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Assessment of energetic renovations for residential buildings by optimization

Bauphysik 2024年第3期46卷 142-153页

作者： Medgenberg, Justus Makowski, Andreas Langner, Normen Technische Hochschule Würzburg-Schweinfurt Fakultät Architektur und Bauingenieurwesen Lehrgebiet für Gebäudetechnik und Klima-Engineering Röntgenring 8 Würzburg 97070 Germany Technische Hochschule Würzburg-Schweinfurt Fakultät Angewandte Natur- und Geisteswissenschaften Ignaz-Schön-Str. 11 Schweinfurt 97421 Germany Technische Hochschule Würzburg-Schweinfurt Fakultät Architektur und Bauingenieurwesen Lehrgebiet Bauphysik Nachhaltigkeit & Baustoffe Röntgenring 8 Würzburg 97070 Germany

Assessment of energetic renovations for residential buildings by optimization. The energetic renovation of existing buildings plays a crucial role in the decarbonization of the building sector. For the best allocation of available resources, a holistic quantification and optimization of renovation decisions is necessary. In this context optimization methods offer potential that has so far hardly been used, especially in German-speaking countries. A new methodology is presented that allows the optimization of variable target functions. The methodology uses a mathematical replacement model based on selective results from dynamic building simulations. The strength of the proposed method lies in the analysis of a very large number of renovation combinations with minimal computational effort. The applicability to real objects is verified using two different exemplary residential building types. The resulting renovation strategies from the analysis are presented for 3 different target cost functions which include investment and operating costs as well as CO₂ emissions under different restrictions. The method can currently be used to assess and optimize the heating demands of residential buildings. For the future different extensions of the methodology are planned. © 2024, Ernst und Sohn. All rights reserved.

关键词： decarbonization strategy economics energetic renovation mathematical optimization meta-model multi-parameter optimization optimization renovation strategy

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Application of a high-performance grey prediction model to predict the cardiovascular disease mortality in elderly Chinese residents

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APPLIED MATHEMATICAL MODELLING 2025年 137卷

作者： Zeng, Bo Yin, Fengfeng Chongqing Technol & Business Univ Sch Management Sci & Engn Chongqing 400067 Peoples R China

With the acceleration of urbanization and aging process, an increasing number of Chinese senior citizens are suffering from cardiovascular diseases (CVDs). Therefore, reducing the prevalence and mortality of CVD has become one of the priorities of the public health department. And the scientific prediction of CVD morality is of great significance in the prevention and treatment of CVD among the elderly. Given the characteristics of "small sample, complex causes and long duration" of CVD among the senior citizens, grey prediction models which aim at handling the data with "small sample, poor information" are more feasible in forecasting its developing trend. In this paper, a new discrete grey prediction model is designed to forecast the CVD morality among Chinese senior citizens, in which a non-linear function is introduced to expand the model structure and the order and background value coefficient are optimized. In all the three sets of experiments, the errors of the new model are close to but smaller than those of the other three mainstream grey prediction models, indicating that the simulation and prediction performance of the new model is more accurate and stable. The research provides a new modelling approach to predicting the CVD mortality among Chinese senior citizens, which is conducive to the prevention of CVD prevalence and the sustainable development of public health.

关键词： Prediction of cardiovascular diseases mortality among Chinese senior citizens Grey prediction model multi-parameter optimization Nonlinear expansion of model structure

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Common-Reflection-Surface Stack with Global Simultaneous multi-parameter Velocity Analysis-A Fit for Shallow Seismics

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APPLIED SCIENCES-BASEL 2024年第15期14卷 6748页

作者： Heilmann, Zeno Deidda, Gian Piero CRS4 Ctr Adv Studies Res & Dev Sardinia Digital Technol Aerosp Dept Loc Piscina Manna I-09050 Pula CA Italy Univ Cagliari Dept Civil & Environm Engn & Architecture Via Marengo 2 I-09123 Cagliari CA Italy

In many regions, particularly coastal areas, population growth, overuse of water, and climate change have put quality and availability of water under threat. While accurate, predictive groundwater flow models are essential for effective water resource management, the precision of these models relies on the ability to determine the geometries of geological structures and hydrogeologic systems accurately. In complex geological settings or with deep aquifers, the drilling of observation wells becomes too costly and shallow seismic surveys become the method of choice. Common-Reflection-Surface stacking is being used by major oil companies for hydrocarbon exploration but can serve also as an advanced imaging method for near-surface seismic data. Its spatial stacking aperture covers a whole group of neighboring common midpoint gathers and, as such, a multitude of traces contribute to every single stacking process. Since the level of noise suppression is proportional to the number of contributing traces, Common-Reflection-Surface stacking generates a large increase in signal-to-noise ratio. In addition, the data-driven velocity analysis is a statistical process and is, as such, the more stable the more input traces it has. At the beginning, however, the spatial operator was only used for stacking, not for velocity analysis, since limiting computational demand was mandatory to obtain results within a reasonable time frame. Today's computing facilities are thousands of times faster and even large efficiency gains do not justify the loss of effectiveness anymore that comes with a truncated velocity analysis. We show that this is particularly true for near-surface data with low signal-to-noise ratio and modest common midpoint fold. For the spatial velocity analysis, we present two options: (1) as reference, a global search of all three parameters of the Common-Reflection-Surface operator, and (2) as a quicker solution, a strategy that uses the two-parameter Common-Diffraction-

关键词： seismic methods groundwaters near-surface CRS stack velocity analysis multi-parameter optimization

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A High-Resolution and Robust Microwave Correlation Imaging Method Based on URRF Using MC-AAMPE Algorithm

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REMOTE SENSING 2024年第18期16卷 3481-3481页

作者： Xue, Min Xing, Mengdao Gao, Yuexin Wu, Zhixin Tang, Wangshuo Wang, Yidi Xidian Univ Natl Key Lab Radar Signal Proc Xian 710071 Peoples R China Xidian Univ Acad Adv Interdisciplinary Res Xian 710071 Peoples R China Xidian Univ Sch Aerosp Sci & Technol Xian 710071 Peoples R China

This manuscript presents a novel framework for high-resolution and robust microwave correlation imaging. In order to generate a more diverse random radiation field distribution, the unified random radiation field (URRF) model is proposed. The URRF model can accurately characterize the joint random modulation in the signals' phase, amplitude, and frequency. Furthermore, we build a parametric imaging model based on URRF which clearly describes the relationship between the image to be reconstructed and the signals by the URRF model. By using this imaging model, the reconstruction of an image is converted into solving a multi-parameter optimization problem with multiple constraints. To solve this optimization problem with high efficiency and accuracy, the model-constrained adaptive alternating multiple parameter estimation (MC-AAMPE) algorithm is proposed. This algorithm decomposes the high-dimensional multi-parameter optimization problem into several sub-optimization problems. The renewing solutions to these sub-optimization problems make the multi-parameter optimization converge to the image of the target and the parameters of clutter and noise, which are all unknown before the solution. In comparison with the existing methods, the proposed scheme generates images with higher resolution and is more robust under noise conditions. Extensive simulation experiments confirmed the effectiveness and robustness of the proposed method.

关键词： microwave correlation imaging unified random radiation field (URRF) multi-parameter optimization model-constrained adaptive alternating multiple parameter estimation (MC-AAMPE)

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optimization of mixing chamber parameters of pavement recycling machine under engineered particle model analysis

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JOURNAL OF THE CHINESE INSTITUTE OF ENGINEERS 2022年第6期45卷 521-531页

作者： Cheng, Haiying Fan, Kangkang Feng, Shiming Seliverstov, N. D. Makarova, D. A. Changan Univ Natl Engn Lab Highway Maintenance Equipment Xian 710064 Shaanxi Peoples R China Inner Mongolia Univ Technol Coll Mech Engn Hohhot Inner Mongolia Peoples R China Moscow Polytech Univ Coll Mech Engn Moscow Russia Moscow State Automobile & Rd Construct Tech Univ Coll Mech Engn Moscow Russia

The structural parameters of the mixing chamber of a pavement recycling machine affect the mixing behavior of an asphalt mixture. Most of the existing studies have used spherical particle models to analyze the mixing behavior, and it is difficult to truly understand the mechanical properties of asphalt mixtures in the mixing chamber. In this study, the discrete element similarity theory and dimensional analysis method were used to establish an engineered asphalt mixture particle model, and the validity of the model was verified by conducting a slump test. Based on these test results, the discrete element method was used to analyze the mixing behavior of the asphalt mixture, and the effect of the structural parameters of the mixing chamber on the mixing time of the asphalt mixture was investigated. The experiment was designed using the orthogonal test method, and a regression model was established based on the experimental data. The PSO algorithm was used to optimize the structural parameters of the mixing chamber. The results show that the mixing time of the coarse aggregate is reduced by 19.31%, the mixing time of the fine aggregate is reduced by 36.36%, and the mixing time of the powder is reduced by 33.33%.

关键词： Pavement recycling machine discrete element method engineered particles multi-parameter optimization particle swarm optimization

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Dynamic finite element simulation of the collision behavior and multi-parameter quantitative characterization of the damage degree of banana fruit in the post-harvest operations

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POSTHARVEST BIOLOGY AND TECHNOLOGY 2025年 219卷

作者： Guo, Jie Yang, Zhou Karkee, Manoj Han, Xiongzhe Duan, Jieli He, Yong Zhejiang Univ Coll Biosyst Engn & Food Sci Hangzhou 310058 Zhejiang Peoples R China South China Agr Univ Coll Engn Guangzhou 510642 Guangdong Peoples R China Washington State Univ Ctr Precis & Automated Agr Syst Prosser WA 99350 USA Kangwon Natl Univ Coll Agr & Life Sci Chunchon 24341 South Korea

Squeezing, collision, friction and other behaviors are widely present in the post-harvest processing operations of bananas, such as field picking, de-handing, cleaning, packaging and transportation, which will inevitably cause a certain degree of mechanical damage to banana fruits. In view of the difficulty in accurately detecting and quantifying fruit damage in the early stage of production, this paper adopted dynamic finite element numerical simulation and multi-parameter optimization of response surface to carry out simulation analysis on the collision behavior of banana fruit in the post-harvest operations, and the accurate assessment and quantitative characterization of fruit damage degree and erosion rule were carried out. The three-dimensional solid model of banana was established by reverse engineering method based on 3D scanning technology. The multi-scale finite element model of banana was further established by combining the constitutive parameters of banana bunch obtained from quasi-static mechanical experiments. In this study, a total of 27 collision systems including different contact materials, collision angles and impact speeds were developed to quantitatively characterize the changing rules of contact force, equivalent stress, energy, damage volume and bruise susceptibility of fruit under different experimental scenarios. An empirical prediction model for banana fruit's bruise susceptibility was established using response surface optimization methodology, and the comprehensive effects of contact material, collision angle and impact speed on fruit damage were obtained. On this basis, three dynamic collision systems including banana hand and impact panel were developed, and the generation region and erosion rule of equivalent stress of banana hand and impact panel under different encounter postures were further investigated. Finally, the physical verification experiments of banana impact and collision were carried out based on the characteristics of b

关键词： Banana fruit Post-harvest operation Damage assessment Dynamic finite element modeling multi-parameter optimization

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multi-Objective Optimal Design of Steel Beams Based on Genetic Algorithm-Response Surface Methodology

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TRANSPORTATION RESEARCH RECORD 2025年

作者： Liu, Hailong Shao, Fei He, Lixiang Xu, Qian Bai, Linyue Army Engn Univ PLA Field Engn Inst Nanjing Peoples R China

Aiming at the complex nonlinear solution of optimizing the design parameters for the static load-carrying capacity of steel beams, this study proposes a multi-parameter optimal design approach for the structure based on the response surface methodology (RSM) surrogate model and the genetic algorithm (GA). First, a finite element model for static calculation of a steel beam is established. Meanwhile, parameter sensitivity is analyzed based on the Plackett-Burman (PB) test design to reduce the dimensionality of the optimization model. Subsequently, utilising the Box-Behnken design (BBD) test method, response surface models for the ultimate load-carrying capacity and the structure mass are fitted to establish the correlation between design variables and response respectively. Then, the optimal solution for RSM and GA-RSM are carried out on the multi-objective optimization of load-carrying capacity and structure mass, respectively. Ultimately, the optimization results are compared and analyzed. The results indicate that the PB test effectively reduces the variable space and computational volume of the response surface model. The prediction accuracy of the models after applying RSM and GA-RSM reaches more than 90% and 99%, respectively. Notably, optimization using GA-RSM yields a reduction of structure mass by 4.5% and an increase of load-carrying capacity by 10.9%, thus verifying its role of serving as a reliable guide for enhancing performance of steel beams. In conclusion, GA-RSM is validated as an effective approach to guide the optimal design of steel beams.

关键词： steel beams experimental design response surface genetic algorithm multi-parameter optimization

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Optimal robust vehicle motion control under equality and inequality constraints

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ASIAN JOURNAL OF CONTROL 2023年第3期25卷 2031-2047页

作者： Zhang, Xinrong Song, Biya Yang, Zeyu Huang, Jin Jia, Yifan Changan Univ Minist Educ Key Lab Highway Construct Technol & Equipment Xian Peoples R China Hunan Univ Coll Mech & Vehicle Engn Changsha Peoples R China Tsinghua Univ Sch Vehicle & Mobil Beijing 100084 Peoples R China

In this paper, a new robust controller is proposed to improve the motion control performance of an autonomous four-wheel steering vehicle. The vehicle is subject to time-varying uncertainties caused by parameter perturbation and unmodeled disturbance. First of all, the vehicle motion control problem is modeled as a constraint-following problem with the goal to drive the vehicle system to follow the given constraints. For safety reasons, inequality constraints are imposed on the lateral displacement of the vehicle. Next, the diffeomorphism mapping method is used to deal with the inequality constraints in the vehicle motion control, and the constrained lateral displacement space is mapped to an unbounded space. On this basis, a new multi-parameter robust constraint-following control is designed. Based on Lyapunov stability theory, the approximate constraint tracking performance of the path tracking system is proved. In order to make a trade-off between the system performance and control cost, a multi-parameter optimization problem is established, and the optimal robust controller is obtained. Last, the main theoretical results are verified by the Carsim-Simulink co-simulations.

关键词： constraint-following diffeomorphism approach equality constraint inequality constraint multi-parameter optimization robust control

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Extending language-based cost functions with deep learning 28

Extending language-based cost functions with deep learning

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Conference on Radar Sensor Technology XXVIII

作者： Zaunegger, Jackson S. Singerman, Paul G. Narayanan, Ram M. Rangaswamy, Muralidhar Penn State Univ University Pk PA 16802 USA Air Force Res Lab Sensors Directorate Wright Patterson AFB OH 45433 USA

ISBN: (纸本)9781510674158;9781510674141

Cognitive radar systems are radar systems that can self-adjust themselves to respond to changes in the environment. Developing cognitive radar systems relies on their ability to detect these changes in operational conditions and use this knowledge to change the operating characteristics of the system, to optimally solve a selected task. Engineers must have an expert level knowledge of radar systems in order to solve these problems as they arise. The goals of the system can be easily stated to engineers in the form of natural language, but are very difficult for computers to analyze. Previous work has shown that Natural Language Processing (NLP) models can be developed to extract radar parameters, values, and units from text. Language Based Cost Functions (LBCFs) can then utilize this extracted information to develop constraints on specific radar parameters. In this work, we propose to combine these language models with LBCFs to define a objective function for optimization tasks using natural language.

关键词： Cognitive Radar Natural Language Processing multi-parameter optimization Language Based Cost Function

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Nonlinear optimization of optical camera multiparameter via triple integrated Gradient-based optimizer algorithm

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OPTICS AND LASER TECHNOLOGY 2024年 179卷

作者： Sun, Kangjian Huo, Ju Jia, Heming Liu, Qi Yang, Jiaming Cai, Chen Harbin Inst Technol Sch Elect Engn & Automat Harbin 150001 Peoples R China Natl Key Lab Modeling & Simulat Complex Syst Harbin 150001 Peoples R China Sanming Univ Sch Informat Engn Sanming 365004 Peoples R China Harbin Inst Technol Sch Astronaut Harbin 150001 Peoples R China China Acad Railway Sci Signal & Commun Res Inst Beijing 100081 Peoples R China

Metaheuristic techniques are widely used to solve various complex real-world problems. Camera calibration is a critical task in machine vision, which aims to determine the optical camera parameters through 2D image features and corresponding 3D spatial features. To overcome the limitations of traditional methods, such as weak local optima avoidance and low calibration accuracy, a triple integrated Gradient-based optimizer (TIGBO_CC) is proposed for nonlinear optimization of optical camera parameters. Several improvements are made to the original Gradient-based optimizer (GBO). First, in the exploration phase, a fitness-distance balance is adopted to select the most contributing candidate to guide the update of the solution. Second, a random search technique is adopted in the exploitation phase. The switching between the original mode and the additional mode follows the probability. Finally, a neighborhood local search is also introduced. Small-step fine search is performed near the optimal solution to improve the quality of the final solution. TIGBO_CC is evaluated on 12 classical functions, the CEC2020 test suite, and the CEC2022 test suite. The experiments include sensitivity analysis, effectiveness analysis, scalability analysis, function value, convergence curve, box plot, Friedman test, Wilcoxon test, etc. Furthermore, a nonlinear camera calibration model is established. Taking the mean reprojection error as the objective function, TIGBO_CC solves the optimal optical camera parameters by minimizing this function. In different scenarios, the calibration method based on TIGBO_CC has high precision and strong reproducibility. Comprehensive analysis shows that TIGBO_CC has excellent optimization ability and practicality.

关键词： Camera calibration multi-parameter optimization Gradient-based optimizer Triple improvement Numerical optimization

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