Many-objective thermodynamic optimization of Stirling heat engine
This paper presents a rigorous investigation of many-objective (four-objective) thermodynamic optimization of a Stirling heat engine. Many-objective optimization problem is formed by considering maximization of thermal efficiency, power output, ecological function and exergy efficiency. Multi-object...
Ausführliche Beschreibung
Autor*in: |
Patel, Vivek [verfasserIn] |
---|
Format: |
E-Artikel |
---|---|
Sprache: |
Englisch |
Erschienen: |
2017transfer abstract |
---|
Schlagwörter: |
---|
Umfang: |
14 |
---|
Übergeordnetes Werk: |
Enthalten in: Rheological analysis of itraconazole-polymer mixtures to determine optimal melt extrusion temperature for development of amorphous solid dispersion - Solanki, Nayan ELSEVIER, 2017, the international journal, Amsterdam [u.a.] |
---|---|
Übergeordnetes Werk: |
volume:125 ; year:2017 ; day:15 ; month:04 ; pages:629-642 ; extent:14 |
Links: |
---|
DOI / URN: |
10.1016/j.energy.2017.02.151 |
---|
Katalog-ID: |
ELV015095355 |
---|
LEADER | 01000caa a22002652 4500 | ||
---|---|---|---|
001 | ELV015095355 | ||
003 | DE-627 | ||
005 | 20230625114537.0 | ||
007 | cr uuu---uuuuu | ||
008 | 180602s2017 xx |||||o 00| ||eng c | ||
024 | 7 | |a 10.1016/j.energy.2017.02.151 |2 doi | |
028 | 5 | 2 | |a GBV00000000000082A.pica |
035 | |a (DE-627)ELV015095355 | ||
035 | |a (ELSEVIER)S0360-5442(17)30334-1 | ||
040 | |a DE-627 |b ger |c DE-627 |e rakwb | ||
041 | |a eng | ||
082 | 0 | |a 600 | |
082 | 0 | 4 | |a 600 |q DE-600 |
082 | 0 | 4 | |a 610 |q VZ |
084 | |a 15,3 |2 ssgn | ||
084 | |a PHARM |q DE-84 |2 fid | ||
084 | |a 44.40 |2 bkl | ||
100 | 1 | |a Patel, Vivek |e verfasserin |4 aut | |
245 | 1 | 0 | |a Many-objective thermodynamic optimization of Stirling heat engine |
264 | 1 | |c 2017transfer abstract | |
300 | |a 14 | ||
336 | |a nicht spezifiziert |b zzz |2 rdacontent | ||
337 | |a nicht spezifiziert |b z |2 rdamedia | ||
338 | |a nicht spezifiziert |b zu |2 rdacarrier | ||
520 | |a This paper presents a rigorous investigation of many-objective (four-objective) thermodynamic optimization of a Stirling heat engine. Many-objective optimization problem is formed by considering maximization of thermal efficiency, power output, ecological function and exergy efficiency. Multi-objective heat transfer search (MOHTS) algorithm is proposed and applied to obtain a set of Pareto-optimal points. Many objective optimization results form a solution in a four dimensional hyper objective space and for visualization it is represented on a two dimension objective space. Thus, results of four-objective optimization are represented by six Pareto fronts in two dimension objective space. These six Pareto fronts are compared with their corresponding two-objective Pareto fronts. Quantitative assessment of the obtained Pareto solutions is reported in terms of spread and the spacing measures. Different decision making approaches such as LINMAP, TOPSIS and fuzzy are used to select a final optimal solution from Pareto optimal set of many-objective optimization. Finally, to reveal the level of conflict between these objectives, distribution of each decision variable in their allowable range is also shown in two dimensional objective spaces. | ||
520 | |a This paper presents a rigorous investigation of many-objective (four-objective) thermodynamic optimization of a Stirling heat engine. Many-objective optimization problem is formed by considering maximization of thermal efficiency, power output, ecological function and exergy efficiency. Multi-objective heat transfer search (MOHTS) algorithm is proposed and applied to obtain a set of Pareto-optimal points. Many objective optimization results form a solution in a four dimensional hyper objective space and for visualization it is represented on a two dimension objective space. Thus, results of four-objective optimization are represented by six Pareto fronts in two dimension objective space. These six Pareto fronts are compared with their corresponding two-objective Pareto fronts. Quantitative assessment of the obtained Pareto solutions is reported in terms of spread and the spacing measures. Different decision making approaches such as LINMAP, TOPSIS and fuzzy are used to select a final optimal solution from Pareto optimal set of many-objective optimization. Finally, to reveal the level of conflict between these objectives, distribution of each decision variable in their allowable range is also shown in two dimensional objective spaces. | ||
650 | 7 | |a Stirling heat engine |2 Elsevier | |
650 | 7 | |a Power output |2 Elsevier | |
650 | 7 | |a Ecological function |2 Elsevier | |
650 | 7 | |a Exergy efficiency |2 Elsevier | |
650 | 7 | |a Many-objective optimization |2 Elsevier | |
650 | 7 | |a Thermal efficiency |2 Elsevier | |
700 | 1 | |a Savsani, Vimal |4 oth | |
700 | 1 | |a Mudgal, Anurag |4 oth | |
773 | 0 | 8 | |i Enthalten in |n Elsevier Science |a Solanki, Nayan ELSEVIER |t Rheological analysis of itraconazole-polymer mixtures to determine optimal melt extrusion temperature for development of amorphous solid dispersion |d 2017 |d the international journal |g Amsterdam [u.a.] |w (DE-627)ELV000529575 |
773 | 1 | 8 | |g volume:125 |g year:2017 |g day:15 |g month:04 |g pages:629-642 |g extent:14 |
856 | 4 | 0 | |u https://doi.org/10.1016/j.energy.2017.02.151 |3 Volltext |
912 | |a GBV_USEFLAG_U | ||
912 | |a GBV_ELV | ||
912 | |a SYSFLAG_U | ||
912 | |a FID-PHARM | ||
912 | |a SSG-OLC-PHA | ||
912 | |a SSG-OPC-PHA | ||
936 | b | k | |a 44.40 |j Pharmazie |j Pharmazeutika |q VZ |
951 | |a AR | ||
952 | |d 125 |j 2017 |b 15 |c 0415 |h 629-642 |g 14 | ||
953 | |2 045F |a 600 |
author_variant |
v p vp |
---|---|
matchkey_str |
patelviveksavsanivimalmudgalanurag:2017----:aybetvtemdnmcpiiainft |
hierarchy_sort_str |
2017transfer abstract |
bklnumber |
44.40 |
publishDate |
2017 |
allfields |
10.1016/j.energy.2017.02.151 doi GBV00000000000082A.pica (DE-627)ELV015095355 (ELSEVIER)S0360-5442(17)30334-1 DE-627 ger DE-627 rakwb eng 600 600 DE-600 610 VZ 15,3 ssgn PHARM DE-84 fid 44.40 bkl Patel, Vivek verfasserin aut Many-objective thermodynamic optimization of Stirling heat engine 2017transfer abstract 14 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier This paper presents a rigorous investigation of many-objective (four-objective) thermodynamic optimization of a Stirling heat engine. Many-objective optimization problem is formed by considering maximization of thermal efficiency, power output, ecological function and exergy efficiency. Multi-objective heat transfer search (MOHTS) algorithm is proposed and applied to obtain a set of Pareto-optimal points. Many objective optimization results form a solution in a four dimensional hyper objective space and for visualization it is represented on a two dimension objective space. Thus, results of four-objective optimization are represented by six Pareto fronts in two dimension objective space. These six Pareto fronts are compared with their corresponding two-objective Pareto fronts. Quantitative assessment of the obtained Pareto solutions is reported in terms of spread and the spacing measures. Different decision making approaches such as LINMAP, TOPSIS and fuzzy are used to select a final optimal solution from Pareto optimal set of many-objective optimization. Finally, to reveal the level of conflict between these objectives, distribution of each decision variable in their allowable range is also shown in two dimensional objective spaces. This paper presents a rigorous investigation of many-objective (four-objective) thermodynamic optimization of a Stirling heat engine. Many-objective optimization problem is formed by considering maximization of thermal efficiency, power output, ecological function and exergy efficiency. Multi-objective heat transfer search (MOHTS) algorithm is proposed and applied to obtain a set of Pareto-optimal points. Many objective optimization results form a solution in a four dimensional hyper objective space and for visualization it is represented on a two dimension objective space. Thus, results of four-objective optimization are represented by six Pareto fronts in two dimension objective space. These six Pareto fronts are compared with their corresponding two-objective Pareto fronts. Quantitative assessment of the obtained Pareto solutions is reported in terms of spread and the spacing measures. Different decision making approaches such as LINMAP, TOPSIS and fuzzy are used to select a final optimal solution from Pareto optimal set of many-objective optimization. Finally, to reveal the level of conflict between these objectives, distribution of each decision variable in their allowable range is also shown in two dimensional objective spaces. Stirling heat engine Elsevier Power output Elsevier Ecological function Elsevier Exergy efficiency Elsevier Many-objective optimization Elsevier Thermal efficiency Elsevier Savsani, Vimal oth Mudgal, Anurag oth Enthalten in Elsevier Science Solanki, Nayan ELSEVIER Rheological analysis of itraconazole-polymer mixtures to determine optimal melt extrusion temperature for development of amorphous solid dispersion 2017 the international journal Amsterdam [u.a.] (DE-627)ELV000529575 volume:125 year:2017 day:15 month:04 pages:629-642 extent:14 https://doi.org/10.1016/j.energy.2017.02.151 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U FID-PHARM SSG-OLC-PHA SSG-OPC-PHA 44.40 Pharmazie Pharmazeutika VZ AR 125 2017 15 0415 629-642 14 045F 600 |
spelling |
10.1016/j.energy.2017.02.151 doi GBV00000000000082A.pica (DE-627)ELV015095355 (ELSEVIER)S0360-5442(17)30334-1 DE-627 ger DE-627 rakwb eng 600 600 DE-600 610 VZ 15,3 ssgn PHARM DE-84 fid 44.40 bkl Patel, Vivek verfasserin aut Many-objective thermodynamic optimization of Stirling heat engine 2017transfer abstract 14 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier This paper presents a rigorous investigation of many-objective (four-objective) thermodynamic optimization of a Stirling heat engine. Many-objective optimization problem is formed by considering maximization of thermal efficiency, power output, ecological function and exergy efficiency. Multi-objective heat transfer search (MOHTS) algorithm is proposed and applied to obtain a set of Pareto-optimal points. Many objective optimization results form a solution in a four dimensional hyper objective space and for visualization it is represented on a two dimension objective space. Thus, results of four-objective optimization are represented by six Pareto fronts in two dimension objective space. These six Pareto fronts are compared with their corresponding two-objective Pareto fronts. Quantitative assessment of the obtained Pareto solutions is reported in terms of spread and the spacing measures. Different decision making approaches such as LINMAP, TOPSIS and fuzzy are used to select a final optimal solution from Pareto optimal set of many-objective optimization. Finally, to reveal the level of conflict between these objectives, distribution of each decision variable in their allowable range is also shown in two dimensional objective spaces. This paper presents a rigorous investigation of many-objective (four-objective) thermodynamic optimization of a Stirling heat engine. Many-objective optimization problem is formed by considering maximization of thermal efficiency, power output, ecological function and exergy efficiency. Multi-objective heat transfer search (MOHTS) algorithm is proposed and applied to obtain a set of Pareto-optimal points. Many objective optimization results form a solution in a four dimensional hyper objective space and for visualization it is represented on a two dimension objective space. Thus, results of four-objective optimization are represented by six Pareto fronts in two dimension objective space. These six Pareto fronts are compared with their corresponding two-objective Pareto fronts. Quantitative assessment of the obtained Pareto solutions is reported in terms of spread and the spacing measures. Different decision making approaches such as LINMAP, TOPSIS and fuzzy are used to select a final optimal solution from Pareto optimal set of many-objective optimization. Finally, to reveal the level of conflict between these objectives, distribution of each decision variable in their allowable range is also shown in two dimensional objective spaces. Stirling heat engine Elsevier Power output Elsevier Ecological function Elsevier Exergy efficiency Elsevier Many-objective optimization Elsevier Thermal efficiency Elsevier Savsani, Vimal oth Mudgal, Anurag oth Enthalten in Elsevier Science Solanki, Nayan ELSEVIER Rheological analysis of itraconazole-polymer mixtures to determine optimal melt extrusion temperature for development of amorphous solid dispersion 2017 the international journal Amsterdam [u.a.] (DE-627)ELV000529575 volume:125 year:2017 day:15 month:04 pages:629-642 extent:14 https://doi.org/10.1016/j.energy.2017.02.151 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U FID-PHARM SSG-OLC-PHA SSG-OPC-PHA 44.40 Pharmazie Pharmazeutika VZ AR 125 2017 15 0415 629-642 14 045F 600 |
allfields_unstemmed |
10.1016/j.energy.2017.02.151 doi GBV00000000000082A.pica (DE-627)ELV015095355 (ELSEVIER)S0360-5442(17)30334-1 DE-627 ger DE-627 rakwb eng 600 600 DE-600 610 VZ 15,3 ssgn PHARM DE-84 fid 44.40 bkl Patel, Vivek verfasserin aut Many-objective thermodynamic optimization of Stirling heat engine 2017transfer abstract 14 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier This paper presents a rigorous investigation of many-objective (four-objective) thermodynamic optimization of a Stirling heat engine. Many-objective optimization problem is formed by considering maximization of thermal efficiency, power output, ecological function and exergy efficiency. Multi-objective heat transfer search (MOHTS) algorithm is proposed and applied to obtain a set of Pareto-optimal points. Many objective optimization results form a solution in a four dimensional hyper objective space and for visualization it is represented on a two dimension objective space. Thus, results of four-objective optimization are represented by six Pareto fronts in two dimension objective space. These six Pareto fronts are compared with their corresponding two-objective Pareto fronts. Quantitative assessment of the obtained Pareto solutions is reported in terms of spread and the spacing measures. Different decision making approaches such as LINMAP, TOPSIS and fuzzy are used to select a final optimal solution from Pareto optimal set of many-objective optimization. Finally, to reveal the level of conflict between these objectives, distribution of each decision variable in their allowable range is also shown in two dimensional objective spaces. This paper presents a rigorous investigation of many-objective (four-objective) thermodynamic optimization of a Stirling heat engine. Many-objective optimization problem is formed by considering maximization of thermal efficiency, power output, ecological function and exergy efficiency. Multi-objective heat transfer search (MOHTS) algorithm is proposed and applied to obtain a set of Pareto-optimal points. Many objective optimization results form a solution in a four dimensional hyper objective space and for visualization it is represented on a two dimension objective space. Thus, results of four-objective optimization are represented by six Pareto fronts in two dimension objective space. These six Pareto fronts are compared with their corresponding two-objective Pareto fronts. Quantitative assessment of the obtained Pareto solutions is reported in terms of spread and the spacing measures. Different decision making approaches such as LINMAP, TOPSIS and fuzzy are used to select a final optimal solution from Pareto optimal set of many-objective optimization. Finally, to reveal the level of conflict between these objectives, distribution of each decision variable in their allowable range is also shown in two dimensional objective spaces. Stirling heat engine Elsevier Power output Elsevier Ecological function Elsevier Exergy efficiency Elsevier Many-objective optimization Elsevier Thermal efficiency Elsevier Savsani, Vimal oth Mudgal, Anurag oth Enthalten in Elsevier Science Solanki, Nayan ELSEVIER Rheological analysis of itraconazole-polymer mixtures to determine optimal melt extrusion temperature for development of amorphous solid dispersion 2017 the international journal Amsterdam [u.a.] (DE-627)ELV000529575 volume:125 year:2017 day:15 month:04 pages:629-642 extent:14 https://doi.org/10.1016/j.energy.2017.02.151 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U FID-PHARM SSG-OLC-PHA SSG-OPC-PHA 44.40 Pharmazie Pharmazeutika VZ AR 125 2017 15 0415 629-642 14 045F 600 |
allfieldsGer |
10.1016/j.energy.2017.02.151 doi GBV00000000000082A.pica (DE-627)ELV015095355 (ELSEVIER)S0360-5442(17)30334-1 DE-627 ger DE-627 rakwb eng 600 600 DE-600 610 VZ 15,3 ssgn PHARM DE-84 fid 44.40 bkl Patel, Vivek verfasserin aut Many-objective thermodynamic optimization of Stirling heat engine 2017transfer abstract 14 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier This paper presents a rigorous investigation of many-objective (four-objective) thermodynamic optimization of a Stirling heat engine. Many-objective optimization problem is formed by considering maximization of thermal efficiency, power output, ecological function and exergy efficiency. Multi-objective heat transfer search (MOHTS) algorithm is proposed and applied to obtain a set of Pareto-optimal points. Many objective optimization results form a solution in a four dimensional hyper objective space and for visualization it is represented on a two dimension objective space. Thus, results of four-objective optimization are represented by six Pareto fronts in two dimension objective space. These six Pareto fronts are compared with their corresponding two-objective Pareto fronts. Quantitative assessment of the obtained Pareto solutions is reported in terms of spread and the spacing measures. Different decision making approaches such as LINMAP, TOPSIS and fuzzy are used to select a final optimal solution from Pareto optimal set of many-objective optimization. Finally, to reveal the level of conflict between these objectives, distribution of each decision variable in their allowable range is also shown in two dimensional objective spaces. This paper presents a rigorous investigation of many-objective (four-objective) thermodynamic optimization of a Stirling heat engine. Many-objective optimization problem is formed by considering maximization of thermal efficiency, power output, ecological function and exergy efficiency. Multi-objective heat transfer search (MOHTS) algorithm is proposed and applied to obtain a set of Pareto-optimal points. Many objective optimization results form a solution in a four dimensional hyper objective space and for visualization it is represented on a two dimension objective space. Thus, results of four-objective optimization are represented by six Pareto fronts in two dimension objective space. These six Pareto fronts are compared with their corresponding two-objective Pareto fronts. Quantitative assessment of the obtained Pareto solutions is reported in terms of spread and the spacing measures. Different decision making approaches such as LINMAP, TOPSIS and fuzzy are used to select a final optimal solution from Pareto optimal set of many-objective optimization. Finally, to reveal the level of conflict between these objectives, distribution of each decision variable in their allowable range is also shown in two dimensional objective spaces. Stirling heat engine Elsevier Power output Elsevier Ecological function Elsevier Exergy efficiency Elsevier Many-objective optimization Elsevier Thermal efficiency Elsevier Savsani, Vimal oth Mudgal, Anurag oth Enthalten in Elsevier Science Solanki, Nayan ELSEVIER Rheological analysis of itraconazole-polymer mixtures to determine optimal melt extrusion temperature for development of amorphous solid dispersion 2017 the international journal Amsterdam [u.a.] (DE-627)ELV000529575 volume:125 year:2017 day:15 month:04 pages:629-642 extent:14 https://doi.org/10.1016/j.energy.2017.02.151 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U FID-PHARM SSG-OLC-PHA SSG-OPC-PHA 44.40 Pharmazie Pharmazeutika VZ AR 125 2017 15 0415 629-642 14 045F 600 |
allfieldsSound |
10.1016/j.energy.2017.02.151 doi GBV00000000000082A.pica (DE-627)ELV015095355 (ELSEVIER)S0360-5442(17)30334-1 DE-627 ger DE-627 rakwb eng 600 600 DE-600 610 VZ 15,3 ssgn PHARM DE-84 fid 44.40 bkl Patel, Vivek verfasserin aut Many-objective thermodynamic optimization of Stirling heat engine 2017transfer abstract 14 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier This paper presents a rigorous investigation of many-objective (four-objective) thermodynamic optimization of a Stirling heat engine. Many-objective optimization problem is formed by considering maximization of thermal efficiency, power output, ecological function and exergy efficiency. Multi-objective heat transfer search (MOHTS) algorithm is proposed and applied to obtain a set of Pareto-optimal points. Many objective optimization results form a solution in a four dimensional hyper objective space and for visualization it is represented on a two dimension objective space. Thus, results of four-objective optimization are represented by six Pareto fronts in two dimension objective space. These six Pareto fronts are compared with their corresponding two-objective Pareto fronts. Quantitative assessment of the obtained Pareto solutions is reported in terms of spread and the spacing measures. Different decision making approaches such as LINMAP, TOPSIS and fuzzy are used to select a final optimal solution from Pareto optimal set of many-objective optimization. Finally, to reveal the level of conflict between these objectives, distribution of each decision variable in their allowable range is also shown in two dimensional objective spaces. This paper presents a rigorous investigation of many-objective (four-objective) thermodynamic optimization of a Stirling heat engine. Many-objective optimization problem is formed by considering maximization of thermal efficiency, power output, ecological function and exergy efficiency. Multi-objective heat transfer search (MOHTS) algorithm is proposed and applied to obtain a set of Pareto-optimal points. Many objective optimization results form a solution in a four dimensional hyper objective space and for visualization it is represented on a two dimension objective space. Thus, results of four-objective optimization are represented by six Pareto fronts in two dimension objective space. These six Pareto fronts are compared with their corresponding two-objective Pareto fronts. Quantitative assessment of the obtained Pareto solutions is reported in terms of spread and the spacing measures. Different decision making approaches such as LINMAP, TOPSIS and fuzzy are used to select a final optimal solution from Pareto optimal set of many-objective optimization. Finally, to reveal the level of conflict between these objectives, distribution of each decision variable in their allowable range is also shown in two dimensional objective spaces. Stirling heat engine Elsevier Power output Elsevier Ecological function Elsevier Exergy efficiency Elsevier Many-objective optimization Elsevier Thermal efficiency Elsevier Savsani, Vimal oth Mudgal, Anurag oth Enthalten in Elsevier Science Solanki, Nayan ELSEVIER Rheological analysis of itraconazole-polymer mixtures to determine optimal melt extrusion temperature for development of amorphous solid dispersion 2017 the international journal Amsterdam [u.a.] (DE-627)ELV000529575 volume:125 year:2017 day:15 month:04 pages:629-642 extent:14 https://doi.org/10.1016/j.energy.2017.02.151 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U FID-PHARM SSG-OLC-PHA SSG-OPC-PHA 44.40 Pharmazie Pharmazeutika VZ AR 125 2017 15 0415 629-642 14 045F 600 |
language |
English |
source |
Enthalten in Rheological analysis of itraconazole-polymer mixtures to determine optimal melt extrusion temperature for development of amorphous solid dispersion Amsterdam [u.a.] volume:125 year:2017 day:15 month:04 pages:629-642 extent:14 |
sourceStr |
Enthalten in Rheological analysis of itraconazole-polymer mixtures to determine optimal melt extrusion temperature for development of amorphous solid dispersion Amsterdam [u.a.] volume:125 year:2017 day:15 month:04 pages:629-642 extent:14 |
format_phy_str_mv |
Article |
bklname |
Pharmazie Pharmazeutika |
institution |
findex.gbv.de |
topic_facet |
Stirling heat engine Power output Ecological function Exergy efficiency Many-objective optimization Thermal efficiency |
dewey-raw |
600 |
isfreeaccess_bool |
false |
container_title |
Rheological analysis of itraconazole-polymer mixtures to determine optimal melt extrusion temperature for development of amorphous solid dispersion |
authorswithroles_txt_mv |
Patel, Vivek @@aut@@ Savsani, Vimal @@oth@@ Mudgal, Anurag @@oth@@ |
publishDateDaySort_date |
2017-01-15T00:00:00Z |
hierarchy_top_id |
ELV000529575 |
dewey-sort |
3600 |
id |
ELV015095355 |
language_de |
englisch |
fullrecord |
<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">ELV015095355</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230625114537.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">180602s2017 xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1016/j.energy.2017.02.151</subfield><subfield code="2">doi</subfield></datafield><datafield tag="028" ind1="5" ind2="2"><subfield code="a">GBV00000000000082A.pica</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)ELV015095355</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(ELSEVIER)S0360-5442(17)30334-1</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="082" ind1="0" ind2=" "><subfield code="a">600</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">600</subfield><subfield code="q">DE-600</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">610</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">15,3</subfield><subfield code="2">ssgn</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">PHARM</subfield><subfield code="q">DE-84</subfield><subfield code="2">fid</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">44.40</subfield><subfield code="2">bkl</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Patel, Vivek</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Many-objective thermodynamic optimization of Stirling heat engine</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2017transfer abstract</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">14</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">nicht spezifiziert</subfield><subfield code="b">zzz</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">nicht spezifiziert</subfield><subfield code="b">z</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">nicht spezifiziert</subfield><subfield code="b">zu</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">This paper presents a rigorous investigation of many-objective (four-objective) thermodynamic optimization of a Stirling heat engine. Many-objective optimization problem is formed by considering maximization of thermal efficiency, power output, ecological function and exergy efficiency. Multi-objective heat transfer search (MOHTS) algorithm is proposed and applied to obtain a set of Pareto-optimal points. Many objective optimization results form a solution in a four dimensional hyper objective space and for visualization it is represented on a two dimension objective space. Thus, results of four-objective optimization are represented by six Pareto fronts in two dimension objective space. These six Pareto fronts are compared with their corresponding two-objective Pareto fronts. Quantitative assessment of the obtained Pareto solutions is reported in terms of spread and the spacing measures. Different decision making approaches such as LINMAP, TOPSIS and fuzzy are used to select a final optimal solution from Pareto optimal set of many-objective optimization. Finally, to reveal the level of conflict between these objectives, distribution of each decision variable in their allowable range is also shown in two dimensional objective spaces.</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">This paper presents a rigorous investigation of many-objective (four-objective) thermodynamic optimization of a Stirling heat engine. Many-objective optimization problem is formed by considering maximization of thermal efficiency, power output, ecological function and exergy efficiency. Multi-objective heat transfer search (MOHTS) algorithm is proposed and applied to obtain a set of Pareto-optimal points. Many objective optimization results form a solution in a four dimensional hyper objective space and for visualization it is represented on a two dimension objective space. Thus, results of four-objective optimization are represented by six Pareto fronts in two dimension objective space. These six Pareto fronts are compared with their corresponding two-objective Pareto fronts. Quantitative assessment of the obtained Pareto solutions is reported in terms of spread and the spacing measures. Different decision making approaches such as LINMAP, TOPSIS and fuzzy are used to select a final optimal solution from Pareto optimal set of many-objective optimization. Finally, to reveal the level of conflict between these objectives, distribution of each decision variable in their allowable range is also shown in two dimensional objective spaces.</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Stirling heat engine</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Power output</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Ecological function</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Exergy efficiency</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Many-objective optimization</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Thermal efficiency</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Savsani, Vimal</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Mudgal, Anurag</subfield><subfield code="4">oth</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="n">Elsevier Science</subfield><subfield code="a">Solanki, Nayan ELSEVIER</subfield><subfield code="t">Rheological analysis of itraconazole-polymer mixtures to determine optimal melt extrusion temperature for development of amorphous solid dispersion</subfield><subfield code="d">2017</subfield><subfield code="d">the international journal</subfield><subfield code="g">Amsterdam [u.a.]</subfield><subfield code="w">(DE-627)ELV000529575</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:125</subfield><subfield code="g">year:2017</subfield><subfield code="g">day:15</subfield><subfield code="g">month:04</subfield><subfield code="g">pages:629-642</subfield><subfield code="g">extent:14</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doi.org/10.1016/j.energy.2017.02.151</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_U</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ELV</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_U</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">FID-PHARM</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OLC-PHA</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OPC-PHA</subfield></datafield><datafield tag="936" ind1="b" ind2="k"><subfield code="a">44.40</subfield><subfield code="j">Pharmazie</subfield><subfield code="j">Pharmazeutika</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">125</subfield><subfield code="j">2017</subfield><subfield code="b">15</subfield><subfield code="c">0415</subfield><subfield code="h">629-642</subfield><subfield code="g">14</subfield></datafield><datafield tag="953" ind1=" " ind2=" "><subfield code="2">045F</subfield><subfield code="a">600</subfield></datafield></record></collection>
|
author |
Patel, Vivek |
spellingShingle |
Patel, Vivek ddc 600 ddc 610 ssgn 15,3 fid PHARM bkl 44.40 Elsevier Stirling heat engine Elsevier Power output Elsevier Ecological function Elsevier Exergy efficiency Elsevier Many-objective optimization Elsevier Thermal efficiency Many-objective thermodynamic optimization of Stirling heat engine |
authorStr |
Patel, Vivek |
ppnlink_with_tag_str_mv |
@@773@@(DE-627)ELV000529575 |
format |
electronic Article |
dewey-ones |
600 - Technology 610 - Medicine & health |
delete_txt_mv |
keep |
author_role |
aut |
collection |
elsevier |
remote_str |
true |
illustrated |
Not Illustrated |
topic_title |
600 600 DE-600 610 VZ 15,3 ssgn PHARM DE-84 fid 44.40 bkl Many-objective thermodynamic optimization of Stirling heat engine Stirling heat engine Elsevier Power output Elsevier Ecological function Elsevier Exergy efficiency Elsevier Many-objective optimization Elsevier Thermal efficiency Elsevier |
topic |
ddc 600 ddc 610 ssgn 15,3 fid PHARM bkl 44.40 Elsevier Stirling heat engine Elsevier Power output Elsevier Ecological function Elsevier Exergy efficiency Elsevier Many-objective optimization Elsevier Thermal efficiency |
topic_unstemmed |
ddc 600 ddc 610 ssgn 15,3 fid PHARM bkl 44.40 Elsevier Stirling heat engine Elsevier Power output Elsevier Ecological function Elsevier Exergy efficiency Elsevier Many-objective optimization Elsevier Thermal efficiency |
topic_browse |
ddc 600 ddc 610 ssgn 15,3 fid PHARM bkl 44.40 Elsevier Stirling heat engine Elsevier Power output Elsevier Ecological function Elsevier Exergy efficiency Elsevier Many-objective optimization Elsevier Thermal efficiency |
format_facet |
Elektronische Aufsätze Aufsätze Elektronische Ressource |
format_main_str_mv |
Text Zeitschrift/Artikel |
carriertype_str_mv |
zu |
author2_variant |
v s vs a m am |
hierarchy_parent_title |
Rheological analysis of itraconazole-polymer mixtures to determine optimal melt extrusion temperature for development of amorphous solid dispersion |
hierarchy_parent_id |
ELV000529575 |
dewey-tens |
600 - Technology 610 - Medicine & health |
hierarchy_top_title |
Rheological analysis of itraconazole-polymer mixtures to determine optimal melt extrusion temperature for development of amorphous solid dispersion |
isfreeaccess_txt |
false |
familylinks_str_mv |
(DE-627)ELV000529575 |
title |
Many-objective thermodynamic optimization of Stirling heat engine |
ctrlnum |
(DE-627)ELV015095355 (ELSEVIER)S0360-5442(17)30334-1 |
title_full |
Many-objective thermodynamic optimization of Stirling heat engine |
author_sort |
Patel, Vivek |
journal |
Rheological analysis of itraconazole-polymer mixtures to determine optimal melt extrusion temperature for development of amorphous solid dispersion |
journalStr |
Rheological analysis of itraconazole-polymer mixtures to determine optimal melt extrusion temperature for development of amorphous solid dispersion |
lang_code |
eng |
isOA_bool |
false |
dewey-hundreds |
600 - Technology |
recordtype |
marc |
publishDateSort |
2017 |
contenttype_str_mv |
zzz |
container_start_page |
629 |
author_browse |
Patel, Vivek |
container_volume |
125 |
physical |
14 |
class |
600 600 DE-600 610 VZ 15,3 ssgn PHARM DE-84 fid 44.40 bkl |
format_se |
Elektronische Aufsätze |
author-letter |
Patel, Vivek |
doi_str_mv |
10.1016/j.energy.2017.02.151 |
dewey-full |
600 610 |
title_sort |
many-objective thermodynamic optimization of stirling heat engine |
title_auth |
Many-objective thermodynamic optimization of Stirling heat engine |
abstract |
This paper presents a rigorous investigation of many-objective (four-objective) thermodynamic optimization of a Stirling heat engine. Many-objective optimization problem is formed by considering maximization of thermal efficiency, power output, ecological function and exergy efficiency. Multi-objective heat transfer search (MOHTS) algorithm is proposed and applied to obtain a set of Pareto-optimal points. Many objective optimization results form a solution in a four dimensional hyper objective space and for visualization it is represented on a two dimension objective space. Thus, results of four-objective optimization are represented by six Pareto fronts in two dimension objective space. These six Pareto fronts are compared with their corresponding two-objective Pareto fronts. Quantitative assessment of the obtained Pareto solutions is reported in terms of spread and the spacing measures. Different decision making approaches such as LINMAP, TOPSIS and fuzzy are used to select a final optimal solution from Pareto optimal set of many-objective optimization. Finally, to reveal the level of conflict between these objectives, distribution of each decision variable in their allowable range is also shown in two dimensional objective spaces. |
abstractGer |
This paper presents a rigorous investigation of many-objective (four-objective) thermodynamic optimization of a Stirling heat engine. Many-objective optimization problem is formed by considering maximization of thermal efficiency, power output, ecological function and exergy efficiency. Multi-objective heat transfer search (MOHTS) algorithm is proposed and applied to obtain a set of Pareto-optimal points. Many objective optimization results form a solution in a four dimensional hyper objective space and for visualization it is represented on a two dimension objective space. Thus, results of four-objective optimization are represented by six Pareto fronts in two dimension objective space. These six Pareto fronts are compared with their corresponding two-objective Pareto fronts. Quantitative assessment of the obtained Pareto solutions is reported in terms of spread and the spacing measures. Different decision making approaches such as LINMAP, TOPSIS and fuzzy are used to select a final optimal solution from Pareto optimal set of many-objective optimization. Finally, to reveal the level of conflict between these objectives, distribution of each decision variable in their allowable range is also shown in two dimensional objective spaces. |
abstract_unstemmed |
This paper presents a rigorous investigation of many-objective (four-objective) thermodynamic optimization of a Stirling heat engine. Many-objective optimization problem is formed by considering maximization of thermal efficiency, power output, ecological function and exergy efficiency. Multi-objective heat transfer search (MOHTS) algorithm is proposed and applied to obtain a set of Pareto-optimal points. Many objective optimization results form a solution in a four dimensional hyper objective space and for visualization it is represented on a two dimension objective space. Thus, results of four-objective optimization are represented by six Pareto fronts in two dimension objective space. These six Pareto fronts are compared with their corresponding two-objective Pareto fronts. Quantitative assessment of the obtained Pareto solutions is reported in terms of spread and the spacing measures. Different decision making approaches such as LINMAP, TOPSIS and fuzzy are used to select a final optimal solution from Pareto optimal set of many-objective optimization. Finally, to reveal the level of conflict between these objectives, distribution of each decision variable in their allowable range is also shown in two dimensional objective spaces. |
collection_details |
GBV_USEFLAG_U GBV_ELV SYSFLAG_U FID-PHARM SSG-OLC-PHA SSG-OPC-PHA |
title_short |
Many-objective thermodynamic optimization of Stirling heat engine |
url |
https://doi.org/10.1016/j.energy.2017.02.151 |
remote_bool |
true |
author2 |
Savsani, Vimal Mudgal, Anurag |
author2Str |
Savsani, Vimal Mudgal, Anurag |
ppnlink |
ELV000529575 |
mediatype_str_mv |
z |
isOA_txt |
false |
hochschulschrift_bool |
false |
author2_role |
oth oth |
doi_str |
10.1016/j.energy.2017.02.151 |
up_date |
2024-07-06T16:44:14.626Z |
_version_ |
1803848782581858304 |
fullrecord_marcxml |
<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">ELV015095355</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230625114537.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">180602s2017 xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1016/j.energy.2017.02.151</subfield><subfield code="2">doi</subfield></datafield><datafield tag="028" ind1="5" ind2="2"><subfield code="a">GBV00000000000082A.pica</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)ELV015095355</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(ELSEVIER)S0360-5442(17)30334-1</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="082" ind1="0" ind2=" "><subfield code="a">600</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">600</subfield><subfield code="q">DE-600</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">610</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">15,3</subfield><subfield code="2">ssgn</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">PHARM</subfield><subfield code="q">DE-84</subfield><subfield code="2">fid</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">44.40</subfield><subfield code="2">bkl</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Patel, Vivek</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Many-objective thermodynamic optimization of Stirling heat engine</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2017transfer abstract</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">14</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">nicht spezifiziert</subfield><subfield code="b">zzz</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">nicht spezifiziert</subfield><subfield code="b">z</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">nicht spezifiziert</subfield><subfield code="b">zu</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">This paper presents a rigorous investigation of many-objective (four-objective) thermodynamic optimization of a Stirling heat engine. Many-objective optimization problem is formed by considering maximization of thermal efficiency, power output, ecological function and exergy efficiency. Multi-objective heat transfer search (MOHTS) algorithm is proposed and applied to obtain a set of Pareto-optimal points. Many objective optimization results form a solution in a four dimensional hyper objective space and for visualization it is represented on a two dimension objective space. Thus, results of four-objective optimization are represented by six Pareto fronts in two dimension objective space. These six Pareto fronts are compared with their corresponding two-objective Pareto fronts. Quantitative assessment of the obtained Pareto solutions is reported in terms of spread and the spacing measures. Different decision making approaches such as LINMAP, TOPSIS and fuzzy are used to select a final optimal solution from Pareto optimal set of many-objective optimization. Finally, to reveal the level of conflict between these objectives, distribution of each decision variable in their allowable range is also shown in two dimensional objective spaces.</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">This paper presents a rigorous investigation of many-objective (four-objective) thermodynamic optimization of a Stirling heat engine. Many-objective optimization problem is formed by considering maximization of thermal efficiency, power output, ecological function and exergy efficiency. Multi-objective heat transfer search (MOHTS) algorithm is proposed and applied to obtain a set of Pareto-optimal points. Many objective optimization results form a solution in a four dimensional hyper objective space and for visualization it is represented on a two dimension objective space. Thus, results of four-objective optimization are represented by six Pareto fronts in two dimension objective space. These six Pareto fronts are compared with their corresponding two-objective Pareto fronts. Quantitative assessment of the obtained Pareto solutions is reported in terms of spread and the spacing measures. Different decision making approaches such as LINMAP, TOPSIS and fuzzy are used to select a final optimal solution from Pareto optimal set of many-objective optimization. Finally, to reveal the level of conflict between these objectives, distribution of each decision variable in their allowable range is also shown in two dimensional objective spaces.</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Stirling heat engine</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Power output</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Ecological function</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Exergy efficiency</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Many-objective optimization</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Thermal efficiency</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Savsani, Vimal</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Mudgal, Anurag</subfield><subfield code="4">oth</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="n">Elsevier Science</subfield><subfield code="a">Solanki, Nayan ELSEVIER</subfield><subfield code="t">Rheological analysis of itraconazole-polymer mixtures to determine optimal melt extrusion temperature for development of amorphous solid dispersion</subfield><subfield code="d">2017</subfield><subfield code="d">the international journal</subfield><subfield code="g">Amsterdam [u.a.]</subfield><subfield code="w">(DE-627)ELV000529575</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:125</subfield><subfield code="g">year:2017</subfield><subfield code="g">day:15</subfield><subfield code="g">month:04</subfield><subfield code="g">pages:629-642</subfield><subfield code="g">extent:14</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doi.org/10.1016/j.energy.2017.02.151</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_U</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ELV</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_U</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">FID-PHARM</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OLC-PHA</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OPC-PHA</subfield></datafield><datafield tag="936" ind1="b" ind2="k"><subfield code="a">44.40</subfield><subfield code="j">Pharmazie</subfield><subfield code="j">Pharmazeutika</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">125</subfield><subfield code="j">2017</subfield><subfield code="b">15</subfield><subfield code="c">0415</subfield><subfield code="h">629-642</subfield><subfield code="g">14</subfield></datafield><datafield tag="953" ind1=" " ind2=" "><subfield code="2">045F</subfield><subfield code="a">600</subfield></datafield></record></collection>
|
score |
7.400296 |