Dr Rajesh Ransing

Athro Cyswllt

Mechanical Engineering

+44 (0) 1792 295219

r.s.ransing@abertawe.ac.uk

303
Trydydd Llawr
Adeilad Gogleddol Peirianneg
Campws y Bae

Ar gael ar gyfer Goruchwyliaeth Ôl-raddedig

Dolenni Ymchwil

https://orcid.org/0000-0003-4848-4545

Trosolwg

Rajesh Ransing

Meysydd Arbenigedd

Dadansoddeg Gweithgynhyrchu
Optimeiddio prosesau a dysgu peirianyddol
Meintioli Ansicrwydd
Meddwl yn seiliedig ar risg, FMEAs a rheoli gwybodaeth sefydliadol
Dadansoddiad cerddediad a cherdded deudroed
Llif hylif ar raddfa nano
Peirianneg Gyfrifiannol

Uchafbwyntiau Gyrfa

Ymchwil

Gwella prosesau ac optimeiddio prosesau gweithgynhyrchu
Meddwl yn seiliedig ar risg a rheoli gwybodaeth sefydliadol
Meintioli ansicrwydd mewn gweithrediadau gweithgynhyrchu
Modelu cyfrifiannol dadansoddiad cerddediad
Dylunio a gweithgynhyrchu dyluniadau prosthetig/orthotig arloesol

Cyhoeddiadau

Uchafbwyntiau Ymchwil

Ransing, R. (2024). Guest editorial: Advancing nanofluid dynamics – a special issue synthesis. International Journal of Numerical Methods for Heat and Fluid Flow, 34(2), 381-382.
https://doi.org/10.1108/hff-02-2024-940, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa66317
Ransing, R., Brown, S., Roshan, H., & Ransing, M. (2017). How to save money in a foundry production with opportunities offered by Industry 4.0 and ISO9001:2015 Standard.. In Plenary Lecture, Jubilee 25th International Scientific and Technical Conference "Foundry production and metallurgy” (pp. 56-64). BNTU.
SU Repository: https://cronfa.swan.ac.uk/Record/cronfa63492
https://rep.bntu.by/handle/data/38803
Batbooti, R. & Ransing, R. (2023). A novel imputation based predictive algorithm for reducing common cause variation from small and mixed datasets with missing values. Computers and Industrial Engineering, 179, 109230
https://doi.org/10.1016/j.cie.2023.109230, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa63117
http://dx.doi.org/10.1016/j.cie.2023.109230
Ransing, R. (2022). Thermal irreversibility demystified. International Journal of Numerical Methods for Heat and Fluid Flow, 33(2)
https://doi.org/10.1108/hff-02-2022-0079, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa60760
Mahmoodi, P., Ransing, R., & Friswell, M. (2016). A novel mathematical formulation for predicting symmetric passive bipedal walking motion with unbalanced masses. Applied Mathematical Modelling, 40(5-6), 3895-3906.
https://doi.org/10.1016/j.apm.2015.10.051, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa26355
Giannetti, C. & Ransing, R. (2016). Risk based uncertainty quantification to improve robustness of manufacturing operations. Computers & Industrial Engineering, 101, 70-80.
https://doi.org/10.1016/j.cie.2016.08.002, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa29528
Ransing, R., Batbooti, R., & Giannetti, C. (2016). A quality correlation algorithm for tolerance synthesis in manufacturing operations. Computers & Industrial Engineering, 93, 1-11.
https://doi.org/10.1016/j.cie.2015.12.008, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa25053
Mahmoodi, P., Aristodemou, S., Ransing, R., Owen, N., & Friswell, M. (2016). Prosthetic foot design optimisation based on roll-over shape and ground reaction force characteristics. Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science
https://doi.org/10.1177/0954406216643110, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa26762
Batbooti, R., Ransing, R., Ransing, M., & Ransing, R. (2016). A bootstrap method for uncertainty estimation in quality correlation algorithm for risk based tolerance synthesis. Computers & Industrial Engineering
https://doi.org/10.1016/j.cie.2016.09.002, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa29741
Hafezi, F., Ransing, R., Lewis, R., & Ransing, R. (2016). The calculation of drag on nano-cylinders. International Journal for Numerical Methods in Engineering, 111(11)
https://doi.org/10.1002/nme.5489, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa31407

Holl Ymchwil

Erthyglau Cylchgronau

Ransing, R. (2024). Guest editorial: Advancing nanofluid dynamics – a special issue synthesis. International Journal of Numerical Methods for Heat and Fluid Flow, 34(2), 381-382.
https://doi.org/10.1108/hff-02-2024-940, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa66317
Batbooti, R. & Ransing, R. (2023). A novel imputation based predictive algorithm for reducing common cause variation from small and mixed datasets with missing values. Computers and Industrial Engineering, 179, 109230
https://doi.org/10.1016/j.cie.2023.109230, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa63117
http://dx.doi.org/10.1016/j.cie.2023.109230
Ransing, R. (2022). Thermal irreversibility demystified. International Journal of Numerical Methods for Heat and Fluid Flow, 33(2)
https://doi.org/10.1108/hff-02-2022-0079, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa60760
Mahmoodi, P., Aristodemou, S., Ransing, R., Owen, N., & Friswell, M. (2016). Prosthetic foot design optimisation based on roll-over shape and ground reaction force characteristics. Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science
https://doi.org/10.1177/0954406216643110, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa26762
Batbooti, R., Ransing, R., Ransing, M., & Ransing, R. (2016). A bootstrap method for uncertainty estimation in quality correlation algorithm for risk based tolerance synthesis. Computers & Industrial Engineering
https://doi.org/10.1016/j.cie.2016.09.002, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa29741
Hafezi, F., Ransing, R., Lewis, R., & Ransing, R. (2016). The calculation of drag on nano-cylinders. International Journal for Numerical Methods in Engineering, 111(11)
https://doi.org/10.1002/nme.5489, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa31407
Charles, W., Mahmoodi, P., Ransing, R., Sazonov, I., & Friswell, M. (2016). Comparison of point foot, collisional and smooth rolling contact models on the bifurcations and stability of bipedal walking. European Journal of Computational Mechanics, 25(3), 273-293.
https://doi.org/10.1080/17797179.2016.1191122, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa31527
http://www.tandfonline.com/doi/full/10.1080/17797179.2016.1191122
Giannetti, C. & Ransing, R. (2016). Risk based uncertainty quantification to improve robustness of manufacturing operations. Computers & Industrial Engineering, 101, 70-80.
https://doi.org/10.1016/j.cie.2016.08.002, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa29528
Ransing, R., Batbooti, R., & Giannetti, C. (2016). A quality correlation algorithm for tolerance synthesis in manufacturing operations. Computers & Industrial Engineering, 93, 1-11.
https://doi.org/10.1016/j.cie.2015.12.008, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa25053
Mahmoodi, P., Ransing, R., & Friswell, M. (2016). A novel mathematical formulation for predicting symmetric passive bipedal walking motion with unbalanced masses. Applied Mathematical Modelling, 40(5-6), 3895-3906.
https://doi.org/10.1016/j.apm.2015.10.051, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa26355
Giannetti, C., Ransing, M., Ransing, R., Bould, D., Gethin, D., & Sienz, J. (2015). Organisational Knowledge Management for Defect Reduction and Sustainable Development in Foundries. International Journal of Knowledge and Systems Science, 6(3), 18-37.
https://doi.org/10.4018/ijkss.2015070102, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa21931
Arjunwadkar, S., Ransing, M., & Ransing, R. (2015). Seven Steps to Energy Efficiency for Foundries. Foundry Management and Technology, 143(3), 24-29.
SU Repository: https://cronfa.swan.ac.uk/Record/cronfa24998
http://foundrymag.com/energy-efficiency
Giannetti, C., Ransing, R., Ransing, M., Bould, D., Gethin, D., & Sienz, J. (2014). A novel variable selection approach based on co-linearity index to discover optimal process settings by analysing mixed data. Computers & Industrial Engineering, 72, 217-229.
https://doi.org/10.1016/j.cie.2014.03.017, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa21495
Ransing, R., Giannetti, C., Ransing, M., James, M., Ransing, R., & Giannetti, C. (2013). A coupled penalty matrix approach and principal component based co-linearity index technique to discover product specific foundry process knowledge from in-process data in order to reduce defects. Computers in Industry, 64(5), 514-523.
https://doi.org/10.1016/j.compind.2013.02.009, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa14574
Mahmoodi, P., Ransing, R., Friswell, M., Friswell, M., & Ransing, R. (2013). Modelling the effect of ‘heel to toe’ roll-over contact on the walking dynamics of passive biped robots. Applied Mathematical Modelling
https://doi.org/10.1016/j.apm.2013.02.048, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa14575
Hafezi, F., Ransing, R., & Ransing, R. (2013). Computational modelling of fluid structure interaction at nano-scale boundaries with modified Maxwellian velocity distribution. Applied Mathematical Modelling
https://doi.org/10.1016/j.apm.2013.04.013, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa14782
Ransing, R. (2011). Enhancing undergraduate student skills to meet research challenges: Case Studies and Examples. The Journal of Engineering Education, XII special issue – Research in State Engineering Colleges in – A Road Map, XXV(1-2)
SU Repository: https://cronfa.swan.ac.uk/Record/cronfa24897
Ransing, R. (2009). An innovative extrusion die layout design approach for single-hole dies. Journal of Materials Processing Technology
https://doi.org/10.1016/j.jmatprotec.2008.07.042, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa5507
R., S., M., P., & Ransing, R. (2006). Optimization in castings—An overview of relevant computational technologies and future challenges. Metallurgical and Materials Transactions B, 37(6), 905-911.
https://doi.org/10.1007/bf02735012, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa24501
Harris, A., Hargreaves, A., Southworth, G., & Ransing, R. (2005). Editorial. School Leadership & Management, 25(4), 317-319.
https://doi.org/10.1080/13634230500197108, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa24510
http://www.scopus.com/inward/record.url?eid=2-s2.0-0842326588&partnerID=MN8TOARS
Ransing, R., Pao, W., Lin, C., Sood, M., Lewis, R., & Ransing, R. (2005). Enhanced medial axis interpolation algorithm and its application to hotspot prediction in a mould–casting assembly. International Journal of Cast Metals Research, 18(1), 1-12.
https://doi.org/10.1179/136404604225022766, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa24505
http://www.scopus.com/inward/record.url?eid=2-s2.0-27444442963&partnerID=MN8TOARS
Postek, E., Lewis, R., Gethin, D., Ransing, R., & Ransing, R. (2005). Influence of initial stresses on the cast behaviour during squeeze forming processes. Journal of Materials Processing Technology, 159(3), 338-346.
https://doi.org/10.1016/j.jmatprotec.2004.05.022, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa24504
http://www.scopus.com/inward/record.url?eid=2-s2.0-11344253035&partnerID=MN8TOARS
Ransing, R., Sood, M., Pao, W., & Ransing, R. (2005). Computer implementation of Heuvers' circle method for thermal optimisation in castings. , 119-126.
https://doi.org/10.1179/136404605225022910, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa1946
Ransing, R., Savino, S., Lewis, R., & Ransing, R. (2005). Numerical optimisation of tilt casting process. , 109-118.
https://doi.org/10.1179/136404605225022901, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa1964
Ransing, R. & Ransing, R. (2004). International Journal of Numerical Methods of Heat and Fluid Flow: Editorial. , 14
SU Repository: https://cronfa.swan.ac.uk/Record/cronfa24509
http://www.scopus.com/inward/record.url?eid=2-s2.0-1842483471&partnerID=MN8TOARS
Ransing, R., Lewis, R., & Gethin, D. (2004). Using a deformable discrete-element technique to model the compaction behaviour of mixed ductile and brittle particulate systems. PHILOSOPHICAL TRANSACTIONS OF THE ROYAL SOCIETY OF LONDON SERIES A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES, 362(1822), 1867-1884.
https://doi.org/10.1098/rsta.2004.1421, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa1963
W.K.S, P., R.S, R., R.W, L., C, L., & Ransing, R. (2004). A medial-axes-based interpolation method for solidification simulation. Finite Elements in Analysis and Design, 40(5-6), 577-593.
https://doi.org/10.1016/s0168-874x(03)00097-0, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa24508
R.W., L., R.S., R., W.K.S., P., K., K., J., B., & Ransing, R. (2004). Alternative techniques for casting process simulation. International Journal of Numerical Methods for Heat & Fluid Flow, 14(2), 145-166.
https://doi.org/10.1108/09615530410513782, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa24507
Gethin, D., Lewis, R., Ransing, R., & Ransing, R. (2003). A discrete deformable element approach for the compaction of powder systems. Modelling and Simulation in Materials Science and Engineering, 11(1), 101-114.
https://doi.org/10.1088/0965-0393/11/1/308, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa24517
http://www.scopus.com/inward/record.url?eid=2-s2.0-0037250837&partnerID=MN8TOARS
Javier, B., Rajesh, R., & Ransing, R. (2003). 10th anniversary conference of ACME-UK. Communications in Numerical Methods in Engineering, 19(9), 657-657.
https://doi.org/10.1002/cnm.624, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa24512
Lewis, R., Ransing, M., Ransing, R., & Ransing, R. (2002). An approach for casting defect analysis employing finite element design optimisation, media axis transformation and neural networks. , 15
SU Repository: https://cronfa.swan.ac.uk/Record/cronfa24520
http://www.scopus.com/inward/record.url?eid=2-s2.0-0036456188&partnerID=MN8TOARS
Cox, I., Lewis, R., Ransing, R., Laszczewski, H., Berni, G., & Ransing, R. (2002). Application of neural computing in basic oxygen steelmaking. Journal of Materials Processing Technology, 120(1-3), 310-315.
https://doi.org/10.1016/S0924-0136(01)01136-0, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa24519
http://www.scopus.com/inward/record.url?eid=2-s2.0-0037080258&partnerID=MN8TOARS
D.T, G., R.S, R., R.W, L., M, D., A.J.L, C., & Ransing, R. (2001). Numerical comparison of a deformable discrete element model and an equivalent continuum analysis for the compaction of ductile porous material. Computers & Structures, 79(13), 1287-1294.
https://doi.org/10.1016/s0045-7949(01)00015-3, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa24521
Lewis, R., Manzari, M., Ransing, R., Gethin, D., & Ransing, R. (2000). Casting shape optimization via process modelling. , 21
SU Repository: https://cronfa.swan.ac.uk/Record/cronfa24525
http://www.scopus.com/inward/record.url?eid=2-s2.0-0033626910&partnerID=MN8TOARS
R.W, L., M.T, M., R.S, R., D.T, G., & Ransing, R. (2000). Casting shape optimisation via process modelling. Materials & Design, 21(4), 381-386.
https://doi.org/10.1016/s0261-3069(99)00079-5, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa24523
R.S, R., D.T, G., A.R, K., P, M., R.W, L., & Ransing, R. (2000). Powder compaction modelling via the discrete and finite element method. Materials & Design, 21(4), 263-269.
https://doi.org/10.1016/s0261-3069(99)00081-3, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa24522
R.W., L., R.S., R., & Ransing, R. (2000). The optimal design of interfacial heat transfer coefficients via a thermal stress model. Finite Elements in Analysis and Design, 34(2), 193-209.
https://doi.org/10.1016/s0168-874x(99)00038-4, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa24524
Ransing, R., Lewis, R., Gethin, D., & Ransing, R. (1999). Lewis-Ransing correlation to optimally design the metal-mould heat transfer. , 9
SU Repository: https://cronfa.swan.ac.uk/Record/cronfa24528
http://www.scopus.com/inward/record.url?eid=2-s2.0-0040631470&partnerID=MN8TOARS
Ransing, R., Gethin, D., Lewis, R., Rowe, R., Roberts, R., & Ransing, R. (1999). Modelling and simulation of the compaction of pharmaceutical powders. , 51
SU Repository: https://cronfa.swan.ac.uk/Record/cronfa24527
http://www.scopus.com/inward/record.url?eid=2-s2.0-4544244255&partnerID=MN8TOARS
R.S., R., R.W., L., D.T., G., & Ransing, R. (1999). Lewis‐Ransing correlation to optimally design the metal‐mould heat transfer. International Journal of Numerical Methods for Heat & Fluid Flow, 9(3), 318-334.
https://doi.org/10.1108/09615539910260167, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa24526
Lewis, R., Ransing, R., & Ransing, R. (1998). Correlation to describe interfacial heat transfer during solidification simulation and its use in the optimal feeding design of castings. , 29
SU Repository: https://cronfa.swan.ac.uk/Record/cronfa24532
http://www.scopus.com/inward/record.url?eid=2-s2.0-0032046050&partnerID=MN8TOARS
Ransing, R., Lewis, R., & Ransing, R. (1998). Recognising patterns in rejection data for diagnosis. , 10
SU Repository: https://cronfa.swan.ac.uk/Record/cronfa24530
http://www.scopus.com/inward/record.url?eid=2-s2.0-24044448329&partnerID=MN8TOARS
R., W., R., S., & Ransing, R. (1998). A correlation to describe interfacial heat transfer during solidification simulation and its use in the optimal feeding design of castings. Metallurgical and Materials Transactions B, 29(2), 437-448.
https://doi.org/10.1007/s11663-998-0122-y, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa24529
Ransing, R., Lewis, R., & Ransing, R. (1997). Optimal design of die coating thickness using the Lewis-Ransing correlation. , 9
SU Repository: https://cronfa.swan.ac.uk/Record/cronfa24535
http://www.scopus.com/inward/record.url?eid=2-s2.0-0042786401&partnerID=MN8TOARS
R., S., R.W., L., & Ransing, R. (1997). A semantically constrained neural network for manufacturing diagnosis. International Journal of Production Research, 35(9), 2639-2660.
https://doi.org/10.1080/002075497194705, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa24533
R., W., R.S., R., & Ransing, R. (1997). A semantically constrained Bayesian network for manufacturing diagnosis. International Journal of Production Research, 35(8), 2171-2188.
https://doi.org/10.1080/002075497194796, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa24534
R., S., M., N., R., W., & Ransing, R. (1995). ICADA: Intelligent computer aided defect analysis for castings. Journal of Intelligent Manufacturing, 6(1), 29-40.
https://doi.org/10.1007/bf00123674, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa24536

Llyfrau Awdurol

Nawi, N., Ransing, R., Salleh, M., Ghazali, R., Hamid, N., & Ransing, R. (2010). Database Theory and Application, Bio-Science and Bio-Technology
https://doi.org/10.1007/978-3-642-17622-7_18, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa24494
http://www.scopus.com/inward/record.url?eid=2-s2.0-78650769143&partnerID=MN8TOARS
Dyson, P., Ransing, R., Williams, P., & Williams, P. (2008). Fluid Properties at Nano/Meso Scale Wiley.
https://doi.org/10.1002/9780470697382, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa5508
Ransing, R., Ransing, M., Lewis, R., & Ransing, R. (2003). On the limitations of neural network techniques for analysing cause and effect relationships in manufacturing processes - A case study
SU Repository: https://cronfa.swan.ac.uk/Record/cronfa24515
http://www.scopus.com/inward/record.url?eid=2-s2.0-2942677405&partnerID=MN8TOARS
Ransing, R., Ransing, M., Lewis, R., & Ransing, R. (2003). The importance of an adaptive gain variation method in back-propagation neural network learning algorithms
SU Repository: https://cronfa.swan.ac.uk/Record/cronfa24513
http://www.scopus.com/inward/record.url?eid=2-s2.0-2942696652&partnerID=MN8TOARS

Cyfraniadau Cynadleddau

Ransing, R., Brown, S., Roshan, H., & Ransing, M. (2017). How to save money in a foundry production with opportunities offered by Industry 4.0 and ISO9001:2015 Standard.. In Plenary Lecture, Jubilee 25th International Scientific and Technical Conference "Foundry production and metallurgy” (pp. 56-64). BNTU.
SU Repository: https://cronfa.swan.ac.uk/Record/cronfa63492
https://rep.bntu.by/handle/data/38803
Ransing, M. & Ransing, R. (2014). “If Only My Foundry Knew What it Knows ...”: A 7Epsilon Perspective on Root Cause Analysis and Corrective Action Plans for ISO9001:2008. In Proceedings of the 61nd Annual Technical Conference on Investment Casting, Covington, KY, USA, October 5-8, 2014
SU Repository: https://cronfa.swan.ac.uk/Record/cronfa24537
https://www.investmentcasting.org/paper_detail.asp?PaperID=999
Roshan , H., Giannetti, C., Ransing, M., & Ransing, R. (2014). “If only my foundry knew what it knows …”: A 7Epsilon perspective on root cause analysis and corrective action plans for ISO9001:2008. In World Foundry Congress 2014
SU Repository: https://cronfa.swan.ac.uk/Record/cronfa24479
Paine, A., Ransing, R., Gethin, D., Sims, G., Richley, J., Boissevain, L., Lewis, M., & Ransing, R. (2013). Challenges faced by a small ship yard in integrating computer aided design and production processes - A real life case study.
SU Repository: https://cronfa.swan.ac.uk/Record/cronfa24491
http://www.scopus.com/inward/record.url?eid=2-s2.0-84903637677&partnerID=MN8TOARS
Nazri, M., Rajesh, S., Meghana, R., & Ransing, R. (2008). A New Method to Improve the Gradient Based Search Direction to Enhance the Computational Efficiency of Back Propagation Based Neural Network Algorithms. In 2008 Second Asia International Conference on Modelling & Simulation (AMS)IEEE.
https://doi.org/10.1109/ams.2008.70, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa24495
Nawi, N., Ransing, M., Ransing, R., & Ransing, R. (2007). Improving the gradient based search direction to enhance training efficiency of back propagation based neural network algorithms.
https://doi.org/10.1007/978-1-84628-663-6-4, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa24498
http://www.scopus.com/inward/record.url?eid=2-s2.0-84881435971&partnerID=MN8TOARS
Nazri, N., Meghana, R., Rajesh, R., & Ransing, R. (2006). An Improved Learning Algorithm Based on The Broyden-Fletcher-Goldfarb-Shanno (BFGS) Method For Back Propagation Neural Networks. In Sixth International Conference on Intelligent Systems Design and ApplicationsIEEE.
https://doi.org/10.1109/isda.2006.95, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa24499
Ransing, R., Sood, M., & Ransing, R. (2005). Review of optimization methods for casting simulation.
SU Repository: https://cronfa.swan.ac.uk/Record/cronfa24503
http://www.scopus.com/inward/record.url?eid=2-s2.0-32544461286&partnerID=MN8TOARS
Ahmad, R., Gethin, D., Lewis, R., Ransing, R., Postek, E., & Ransing, R. (2005). Thermal optimisation of the squeeze-forming process using genetic algorithms.
SU Repository: https://cronfa.swan.ac.uk/Record/cronfa24502
http://www.scopus.com/inward/record.url?eid=2-s2.0-80053436937&partnerID=MN8TOARS
Lewis, R., Postek, E., Ransing, R., Han, Z., Gethin, D., & Ransing, R. (2004). A finite element model of the squeeze casting process.
SU Repository: https://cronfa.swan.ac.uk/Record/cronfa24511
http://www.scopus.com/inward/record.url?eid=2-s2.0-84893519303&partnerID=MN8TOARS
Malan, A., Lewis, R., Ransing, R., & Ransing, R. (2003). Modeling Coupled Heat and Mass Transfer in Drying Capillary Hygroscopic and Non-hygroscopic Porous Materials.
SU Repository: https://cronfa.swan.ac.uk/Record/cronfa24516
http://www.scopus.com/inward/record.url?eid=2-s2.0-0142209292&partnerID=MN8TOARS
Ransing, R., Pao, W., Lewis, R., & Ransing, R. (2003). Solidification and thermal stress simulation using medial objects.
SU Repository: https://cronfa.swan.ac.uk/Record/cronfa24514
http://www.scopus.com/inward/record.url?eid=2-s2.0-0142240290&partnerID=MN8TOARS
X., S., R., W., D., T., R., S., R., C., & Ransing, R. (2002). Discrete-Finite Element Modelling of Pharmaceutical Powder Compaction: A Two-Stage Contact Detection Algorithm for Non-Spherical Particles. In Discrete Element MethodsAmerican Society of Civil Engineers.
https://doi.org/10.1061/40647(259)14, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa24518
Lewis, R., Cross, J., Gethin, D., Ransing, R., Manzari, M., Rahman, N., & Ransing, R. (1998). Recent developments in heat transfer and porous media.
SU Repository: https://cronfa.swan.ac.uk/Record/cronfa24531
http://www.scopus.com/inward/record.url?eid=2-s2.0-0032275225&partnerID=MN8TOARS

Cynnyrch Ymchwil Arall

Ransing, R. & Ransing, R. (2010). Back to basics: Process optimisation using in-process data
SU Repository: https://cronfa.swan.ac.uk/Record/cronfa24493
http://www.scopus.com/inward/record.url?eid=2-s2.0-78650875982&partnerID=MN8TOARS
Ransing, R. & Ransing, R. (2010). Challenges in investment casting process control
SU Repository: https://cronfa.swan.ac.uk/Record/cronfa24492
http://www.scopus.com/inward/record.url?eid=2-s2.0-77954331787&partnerID=MN8TOARS
Nazri, M., Meghana, R., Rajesh, S., & Ransing, R. (2007). Research and Development in Intelligent Systems XXIII
https://doi.org/10.1007/978-1-84628-663-6_4, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa24497
Ransing, R., Ransing, M., & Ransing, R. (2007). Innovations in machine learning and defect diagnostics
SU Repository: https://cronfa.swan.ac.uk/Record/cronfa24496
http://www.scopus.com/inward/record.url?eid=2-s2.0-34250874412&partnerID=MN8TOARS
Ransing, R. & Ransing, R. (2006). Software solutions: Recall with X1Recall.com
SU Repository: https://cronfa.swan.ac.uk/Record/cronfa24500
http://www.scopus.com/inward/record.url?eid=2-s2.0-33644511088&partnerID=MN8TOARS
Ransing, R. & Ransing, R. (2005). 'Thinking' software set to revolutionise defect analysis
SU Repository: https://cronfa.swan.ac.uk/Record/cronfa24506
http://www.scopus.com/inward/record.url?eid=2-s2.0-18844425207&partnerID=MN8TOARS

Goruchwyliaeth

A Multi-Modal Digital Twinning Framework for Root Cause Analysis and Risk Management in Smart Manufacturing (cyfredol)

PhD

Goruchwyliwr arall: Prof Mike Jennings
Evolution of computational tools and experimental methods for the development of passive prosthetic feet. (dyfarnwyd 2022)

EngD

Goruchwyliwr arall: Dr Nicholas Owen
An investigation into the sterilisation capabilities of biopolymers and the introduction of an organisational knowledge management methodology for the medical device industry. (dyfarnwyd 2022)

MSc

Goruchwyliwr arall: Dr Will Harrison

Modiwlau a Addysgir

EG-261 Thermodynamics 2

In the second-year thermodynamics course, students learn about using heat energy to generate power. As we face resource challenges in 2050, making energy use efficient is very important. But just being efficient isn't enough. We also need to move away from the combustion of fossil fuels. We must explore innovative pathways to unlock the complete work potential of thermal energy. This is where the invaluable insights derived from the laws of thermodynamics, and in particular the entropy generation term, come into play. The main goal of this module is to teach students two key ideas: thermodynamic efficiency and irreversibility. These ideas are used in different processes where heat is turned into work and vice versa. Throughout the course, students will encounter practical engineering examples, involving steady and unsteady flow systems, which encompass heat, work, and/or mass transfer. By understanding thermodynamics well, students will gain the knowledge and skills needed to improve how we use energy in a world with limited resources. This deep understanding will equip them to tackle the challenges of optimising energy utilisation in a resource-constrained future.
EG-M93 Metallurgy and Alloy Design

The module will be presented with real life scenario of improving mechanical properties of a cast component by providing suggestions for optimising its alloy composition. The module will cover the necessary knowledge required to understand the metallurgical concepts and terminology used in peer-reviewed scientific papers so that students can not only review them but evaluate results and use the information to make informed decisions in the context of alloy design.

Dr Rajesh Ransing

Rhif ffôn

Cyfeiriad ebost