Application of ADAMS in the Optimization Design of Automobile Double Cross Shaft Universal Joint Steering Transmission System by Pan Yu, He Yunfeng, Xie Weijia, He Zhibing, Li Changyou, Huang Yuandu

“…Aiming at the problem of speed fluctuation caused by the hard dot arrangement of the automobile double cross shaft universal joint steering system,the layout of hard spot how to ensure universal constant velocity transmission is studied,and taking the double cross shaft universal joint transmission structural optimization of a car as example,by using ADAMS / view software,the parametric dynamics model of double cross shaft universal joint transmission mechanism is built.Taking the variable in structure as design variable,taking the interaxial angle between intermediate shaft and the input shaft,the output shaft is not less than 155° as constraint condition,taking the angular difference of interaxial angle between intermediate shaft and the driving,driven shaft as the optimization target,and setting the steering intermediate shaft phase angle,the best hard spot layout program of double cross shaft universal joint steering system is acquired,and the steering transmission without fluctuation.…”
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Optimizing heat transfer in a finned rectangular latent heat storage system using response surface methodology by Mohammadreza Ebrahimnataj Tiji, Sina Rezaei, Khashayar Hosseinzadeh, Sami Kaplan, Pouyan Talebizadehsardari, Amir Keshmiri

“…This work explores how fin design optimization can improve heat transfer in latent heat thermal energy storage (LHTES) systems. …”
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Comparative study of thermohydraulic performance in mini-channel heat sink systems: Multi-objective optimization and exergy considerations by Zouheyr Noui, Mohamed Si-Ameur, Nabil Bessanane, Amel Djebara, Adnan Ibrahim, Muhammad Amir Aziat Bin Ishak, Raheem K. Ajeel, Sharul Sham Dol

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Fundamental limits to the generation of highly displaced bright squeezed light using linear optics and parametric amplifiers by Steve M. Young, Daniel Soh

“…We explore the nature and extent of these trade-offs specific to each mechanism and identify the optimal operation modes for each. Finally, we identify the conditions for minimum-uncertainty squeezing in arbitrary parametric amplifying systems and show that displacing the output signal will in general violate these conditions, adding noise and degrading squeezing.…”
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Unique thermal architecture integrating heliostat solar fields with a dual-loop power generation cycle employing thermoelectric; thermal/financial study and GA optimization by Amr S. Abouzied, Xiaoming Guo, Azher M. Abed, Mohammed A. Alghassab, Fahad M. Alhomayani, Baseem Khan, Yasser Elmasry, Ahmad Almadhor, Salem Alkhalaf, Albara Ibrahim Alrawashdeh

“…Furthermore, a parametric analysis has been executed to investigate the effects of critical parameters on the system's operational efficiency. …”
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Hybrid-Driven Dynamic Position Prediction of Robot End-Effector Integrating Parametric Dynamic Model and Machine Learning by Hepeng Ni, Cong Xu, Yingxin Ye, Bo Chen, Shuangsheng Luo, Shuai Ji

“…Accurate dynamic model and response prediction of industrial robots (IRs) are prerequisites for production optimization before actual operation. In this study, a hybrid-driven dynamic position prediction (HDPP) approach integrating a parametric dynamic model (PDM) and learning-based residual error compensators (RECs) is developed to estimate the actual position of a robot end-effector based on the reference input trajectory. …”
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A Component-Based Parametric Reduced-Order Modeling Method Combined with Substructural Matrix Interpolation and Automatic Sampling by Ying Liu, Hongguang Li, Yun Li, Huanyu Du

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Structural Damage Identification through an Optimal Sensor Placement Approach and the Modal Strain Energy Based Index by Seyed Mohammad Seyedpoor, Reza Yahyapour, Ali Asghar Mofdi, Saeed Fallahian

“…In the first stage, a correlation function between the reconstructed mode shapes using the iterated improved reduced system (IRS) method and the complete mode shapes of a structure is defined and then the function is minimized via the binary differential evolution (BDE) algorithm to find the optimal sensor placement of the structure. …”
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Waste heat recovery cycles integration into a net-Zero emission solar-thermal multi-generation system; Techno-economic analysis and ANN-MOPSO optimization by Pradeep Kumar Singh, Ali Basem, Rebwar Nasir Dara, Mohamed Shaban, Sarminah Samad, Raymond Ghandour, Ahmad Almadhor, Samah G. Babiker, Iskandar Shernazarov, Ibrahim A. Alsayer

“…Finally, under optimal conditions, the system achieves an exergy efficiency of 31.69 %, freshwater production of 19.53 kg/s, cooling production of 441.6 kW, and a total cost rate of $87.2/h.…”
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Digital Design Platform of RV Reducer by Minghui Xu, Wanli Li

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Performance Improvement of a Flash-Binary Geothermal Power System Using Zeotropic Working Fluid; A Comprehensive Exergoeconomic Analysis and Optimization by Seyed Sajad Mosaviasl, Ali Dezhdar, Sajjad Keykhah, Ehsan Farhadi, Mojtaba Nedaei

“…Then, a parametric study is performed to obtain the effect of vapor generator temperature and zeotropic mixture’s mass fraction on the proposed system’s main performance criteria. …”
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Classification and risk assessment of ovarian-adnexal lesions using parametric and radiomic analysis of co-registered ultrasound-photoacoustic tomographic images by Yixiao Lin, Quing Zhu

“…Ovarian-adnexal lesions are conventionally assessed with ultrasound (US) under the guidance of the Ovarian-Adnexal Reporting and Data System (O-RADS). However, the low specificity of O-RADS results in many unnecessary surgeries. …”
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Thermodynamic performance of organic rankine cycle based pumped thermal energy storage system with different working fluids by Zhongrong Liang, Guo Zheng, Guowei Wu, Zilin Pan, Zongquan Hu, Min Xu, Hongwei Chen

“…Five working fluids—R245fa, isobutane, isopentane, MM, and R1336mzz(Z)—are selected for analysis based on parametric evaporation temperature (T1) and thermal storage temperature (T8).Parameter analysis results reveal that both round-trip efficiency (ηptp) and exergy efficiency (ηex) increase with rising T1, with the system using MM demonstrating optimal performance: at T1 of 70 °C, ηptp reaches 71.34 %, and ηex is 37.42 %. …”
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MORKO: A Multi-objective Runge–Kutta Optimizer for Multi-domain Optimization Problems by Kanak Kalita, Pradeep Jangir, Sundaram B. Pandya, Ahmed Ibrahim Alzahrani, Fahad Alblehai, Laith Abualigah, Absalom E. Ezugwu

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Multi scenario chaotic transient search optimization algorithm for global optimization technique by Ibrahim Mohamed Diaaeldin, Hany M. Hasanien, Mohammed H. Qais, Saad Alghuwainem, Othman A. M. Omar

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Multi-Objective Optimization of Energy, Exergy, Exergoeconomic Analyses a Double-Pessure Flash-Binary Geothermal Power System Using Zeotropic Working Fluid by Arivalagan Pugazhendhi, Van Vang

“…Parametric study is conducted to study the effect of some main parameters variation on the proposed system performance. …”
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<inline-formula><tex-math notation="LaTeX">$\mathcal {H}_{2}$</tex-math></inline-formula>- and <inline-formula><tex-math notation="LaTeX">$\mathcal {H}_\infty$</tex-math></inline-f... by Abhishek Pandala, Aaron D. Ames, Kaveh Akbari Hamed

“…The system is then analyzed to accommodate parametric uncertainties and to synthesize robust optimal <inline-formula><tex-math notation="LaTeX">$\mathcal {H}_{2}$</tex-math></inline-formula> and <inline-formula><tex-math notation="LaTeX">$\mathcal {H}_\infty$</tex-math></inline-formula> feedback controllers via linear matrix inequalities (LMIs). …”
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Distributionally Robust Policy and Lyapunov-Certificate Learning by Kehan Long, Jorge Cortes, Nikolay Atanasov

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A global approach to detecting and characterizing water leakage in a concrete bridge deck: Parametric study to validate an adapted Full-Waveform Inversion method by Viktoriia Buliuk, Amine Ihamouten, Christophe Heinkele, Xavier Dérobert

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Stochastic Modeling and Availability Optimization of Nuts Manufacturing Plant Using Markov Process and Particle Swarm Optimization by Naveen Kumar, Ashish Kumar, Deepak Sinwar, Monika Saini

“…The objective function is optimized using particle swarm optimization to predict the optimal availability and estimated parametric values. …”
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