Lunar In Situ Large-Scale Construction:Quantitative Evaluation of Regolith Solidification Techniques

Lunar habitat construction is crucial for successful lunar exploration missions.Due to the limitations of transportation conditions,extensive global research has been conducted on lunar in situ material processing techniques in recent years.The aim of this paper is to provide a comprehensive review,precise classification,and quantitative evaluation of these approaches,focusing specifically on four main approaches:reaction solidification(RS),sintering/melting(SM),bonding solidification(BS),and confinement formation(CF).Eight key indicators have been identified for the construction of low-cost and highperformance systems to assess the feasibility of these methods:in situ material ratio,curing temperature,curing time,implementation conditions,compressive strength,tensile strength,curing dimensions,and environmental adaptability.The scoring thresholds are determined by comparing the construction requirements with the actual capabilities.Among the evaluated methods,regolith bagging has emerged as a promising option due to its high in situ material ratio,low time requirement,lack of hightemperature requirements,and minimal shortcomings,with only the compressive strength falling below the neutral score.The compressive strength still maintains a value of 2–3 MPa.The proposed construction scheme utilizing regolith bags offers numerous advantages,including rapid and large-scale construction,ensured tensile strength,and reduced reliance on equipment and energy.In this study,guidelines for evaluating regolith solidification techniques are provided,and directions for improvement are offered.The proposed lunar habitat design based on regolith bags is a practical reference for future research.

Optical fiber FBG linear sensing systems for the on-line monitoring of airborne high temperature air duct leakage

Electrical sensing systems, such as those involving eutectic salt, are mostly used in connection to leakage from existing airborne high-temperature air-conducting pipelines. Such complex structured systems are susceptible to external interferences and, thus, cannot meet the increasingly strict monitoring needs of a complex air-conducting pipeline system of an aircraft. In view of this point, this paper studies an alternative sensor system based on a dense array fiber grating. To obtain a compact and light-weight airborne signal processing system, a field programmable gate array is used as the main control core that controls the output of the light source. The functions of pulse modulation, analog-to-digital conversion,data buffering and transmission are integrated into a single system, while the linear sensing monitoring is obtained by detecting the time-division and wavelength-division wavelength drift signals of the fiber Bragg grating array. Our experiments show that the spatial resolution of the linear sensing system approaches 5 cm, the temperature measurement accuracy reaches 2 ℃, the temperature measurement range is between 0–250 ℃, and the response time is within 4 s. Compared with the existing electrical monitoring systems, various monitoring indicators have been greatly improved and have broad application prospects.

Utilizing interpretable stacking ensemble learning and NSGA-Ⅲ for the prediction and optimisation of building photo-thermal environment and energy consumption

This study develops an approach consisting of a stacking model integrated with a multi-objective optimisation algorithm aimed at predicting and optimising the ecological performance of buildings.The integrated model consists of five base models and a meta-model,which significantly improves the prediction performance.Specifically,the R2 value was improved by 9.19% and the error metrics MAE,MSE,MAPE,and CVRMSE were reduced by 69.47%,79.88%,67.32%,and 57.02%,respectively,compared to the single prediction model.According to the research on interpretable machine learning,adding the SHAP value gives us a deeper understanding of the impact of each architectural design parameter on the performance.In the multi-objective optimisation part,we used the NSGA-Ⅲ algorithm to successfully improve the energy efficiency,daylight utilisation and thermal comfort of the building.Specifically,the optimal design solution reduces the energy use intensity by 31.6 kWh/m^(2),improves the useful daylight index by 39%,and modulated the thermal comfort index,resulting in a decrement of 0.69℃ for the summer season and an enhancement of 0.64℃ for the winter season,respectively.Overall,this study provides building designers and decision makers with a tool to make better design decisions at an early stage to achieve a better combination of energy efficiency,daylight utilisation and thermal comfort optimisation in an integrated manner,providing an important support for achieving sustainable building design.