Universal Approximation of Parametric Optimization via Neural Networks with Piecewise Linear Policy Approximation

Parametric optimization solves a family of optimization problems as a function of parameters. It is a critical component in situations where optimal decision making is repeatedly performed for updated parameter values, but computation becomes challenging when complex problems need to be solved in real-time. Therefore, in this study, we present theoretical foundations on approximating optimal policy of parametric optimization problem through Neural Networks and derive conditions that allow the Universal Approximation Theorem to be applied to parametric optimization problems by constructing piecewise linear policy approximation explicitly. This study fills the gap on formally analyzing the constructed piecewise linear approximation in terms of feasibility and optimality and show that Neural Networks (with ReLU activations) can be valid approximator for this approximation in terms of generalization and approximation error. Furthermore, based on theoretical results, we propose a strategy to improve feasibility of approximated solution and discuss training with suboptimal solutions.Comment: 17 pages, 2 figures, preprint, under revie

Determining Adaptability Performance of Artificial Neural Network-Based Thermal Control Logics for Envelope Conditions in Residential Buildings

This is the publisher's version, also available electronically from http://www.mdpi.com/1996-1073/6/7/3548This study examines the performance and adaptability of Artificial Neural Network (ANN)-based thermal control strategies for diverse thermal properties of building envelope conditions applied to residential buildings. The thermal performance using two non-ANN-based control logics and two predictive ANN-based control logics was numerically tested using simulation software after validation. The performance tests were conducted for a two-story single-family house for various envelope insulation levels and window-to-wall ratios on the envelopes. The percentages of the period within the targeted ranges for air temperature, humidity and PMV, and the magnitudes of the overshoots and undershoots outside of the targeted comfort range were analyzed for each control logic scheme. The results revealed that the two predictive control logics that employed thermal predictions of the ANN models achieved longer periods of thermal comfort than the non-ANN-based models in terms of the comfort periods and the reductions of the magnitudes of the overshoots and undershoots. The ANN-based models proved their adaptability through accurate control of the thermal conditions in buildings with various architectural variables. The ANN-based predictive control methods demonstrated their potential to create more comfortable thermal conditions in single-family homes compared to non-ANN based control logics

Properties of CLC According to Replacement Ratio of Cao-CSA Expansive Additive

According to the National Statistical Office\u27s 2019 Population and Housing Survey in August 2020, the number of apartments, including apartments, was about 14 million last year, accounting for 77.2% of all houses, of which 11.287 million were 80.6% of apartments. Based on this change in housing trends, researchers have developed and studied cellular light-weight concrete (CLC) that can be cured at room temperature and normal pressure with advantages such as light weight, insulation, and construction. There have been several studies in Korea, including state-run projects, but they have not been commercialized, but the biggest reason is that stability has not been secured. Therefore, to improve the reliability of CLC that can be cured at normal temperature and pressure, this study attempts to analyze the properties of CLC by incorporating CaO-CSA expansive additive. Based on the drying density of 0.55-0.65 kg/m3, cement, blast furnace slag, animal foaming additive and fiber are utilized to analyze the properties of CLC with CaO-CSA expansive and the results are as follows. By using the CaO-CSA expansive additive, it is determined that the formation of calcium hydroxide and ettringite fills the CLC between the tobermorite layers and the internal structure becomes dense. Currently, based on KS F 2701, the compression strength based on 0.6 items is more than 4.9 MPa, and the strength is about twice as strong as that of the existing CLC, and durability of the CLC are improved by incorporating CaO-CSA expansive additive

Bridge damage detection using probability distribution of RMSE values of moving vehicle acceleration

The 20th working conference of the IFIP Working Group 7.5 on Reliability and Optimization of Structural Systems (IFIP 2022) will be held at Kyoto University, Kyoto, Japan, September 19-20, 2022.In recent years, indirect bridge health monitoring methods using sensors mounted on measuring vehicles, known as drive-by methods, have received increasing attention. This study intends to investigate the feasibility of a drive-by bridge health monitoring method utilizing moving vehicle accelerations. The proposed method investigates whether there is any abnormality in the bridge by using the subtraction between the preliminary-measured vehicle acceleration when the bridge is healthy and the newly-measured vehicle acceleration when the bridge is tested. A band pass filter is applied to the vehicle accelerations before the subtraction in order to eliminate undesirable vibration components other than the frequency of the first bending mode of the bridge. The damage existence and level are investigated by calculating the RMS of the difference between the preliminary-measured and newly-measured accelerations of the vehicle. Considering the variation in the measurements, several measurements are conducted, and the RMS (Root Means Square) values and their probability distributions are examined. The laboratory experiment using a test vehicle equipped with accelerometers was conducted. Observations through this study demonstrated that the proposed method successfully determined the bridge damage existence and its level in a certain accuracy when the frequency of the first mode of the bridge varies with the damage of the bridge