A MODEL FOR PROGRAMMING DESIGN INTERVENTIONS AIMED AT REDUCING THERMAL DISCOMFORT IN URBAN OPEN SPACES:A Case Study on the Politecnico di Milano Campus

The environmental quality of urban spaces is strongly related to the thermal comfort perceived by people in open areas.At the micro-scale of neighbourhoods,the mitigation of the heat island effect can improve both the well-being of cityusers in the public realm and the energy performance of buildings.A model intended for urban designers is presented,and it sets out to evaluate critical areas in the city context and define sustainable design solutions and concrete actions on the physical environment,in order to increase thermal comfort.In particular,variables used in the model are basically related to urban geometry,such as the accessibility of sunlight,sky view factors,aspect ratios of street canyons,and to the physical materials in the city,such as the albedo of horizontal and vertical surfaces and vegetation density.The technique is based on the use of algorithms defi ned in a Matlab environment and derived from image processing of Digital Elevation Models(DEMs)of the urban texture.The application was tested on the case study of the Politecnico di Milano’s main campus,located in the city of Milan.Especially in the case of limited resources,the results of the analysis suggest how public administrators and decision-makers could benefi t from programming specific site interventions,based on the identification of critical weaknesses emerging at several points in the city.Moreover,the study focuses on the application of cool surfaces,the role of building layout(shape and size)and the effects of increasing the vegetation.Even in the absence of expensive thermal imagery from remote sensing,but simply referring to available cartography,this low-cost technique makes it possible to very quickly set up feasible environmental strategies over extensive urban areas.Furthermore,this tool proves to be useful for existing urban areas,as well as for simulating the impact of new design schemes.

Machine learning applications on lunar meteorite minerals:From classification to mechanical properties prediction

Amid the scarcity of lunar meteorites and the imperative to preserve their scientific value,nondestructive testing methods are essential.This translates into the application of microscale rock mechanics experiments and scanning electron microscopy for surface composition analysis.This study explores the application of Machine Learning algorithms in predicting the mineralogical and mechanical properties of DHOFAR 1084,JAH 838,and NWA 11444 lunar meteorites based solely on their atomic percentage compositions.Leveraging a prior-data fitted network model,we achieved near-perfect classification scores for meteorites,mineral groups,and individual minerals.The regressor models,notably the KNeighbor model,provided an outstanding estimate of the mechanical properties—previously measured by nanoindentation tests—such as hardness,reduced Young’s modulus,and elastic recovery.Further considerations on the nature and physical properties of the minerals forming these meteorites,including porosity,crystal orientation,or shock degree,are essential for refining predictions.Our findings underscore the potential of Machine Learning in enhancing mineral identification and mechanical property estimation in lunar exploration,which pave the way for new advancements and quick assessments in extraterrestrial mineral mining,processing,and research.

Clarification of underneath capacity loss for O3-type Ni, co free layered cathodes at high voltage for sodium ion batteries

Earth abundant O3-type NaFe_(0.5)Mn_(0.5)O_(2)layered oxide is regarded as one of the most promising cathodes for sodium ion batteries due to its low cost and high energy density.However,its poor structural stability and cycle life strongly impede the practical application.Herein,the dynamic phase evolution as well as charge compensation mechanism of O3-type NaFe_(0.5)Mn_(0.5)O_(2)cathode during sodiation/desodiation are revealed by a systemic study with operando X-ray diffraction and X-ray absorption spectroscopy,high resolution neutron powder diffraction and neutron pair distribution functions.The layered structure experiences a phase transition of O3→P3→OP2→ramsdellite during the desodiation,and a new O3’phase is observed at the end of the discharge state(1.5 V).The density functional theory(DFT)calculations and nPDF results suggest that depletion of Na^(+)ions induces the movement of Fe into Na layer resulting the formation of an inert ramsdellite phase thus causing the loss of capacity and structural integrity.Meanwhile,the operando XAS clarified the voltage regions for active Mn^(3+)/Mn^(4+)and Fe^(3+)/Fe^(4+)redox couples.This work points out the universal underneath problem for Fe-based layered oxide cathodes when cycled at high voltage and highlights the importance to suppress Fe migration regarding the design of high energy O3-type cathodes for sodium ion batteries.

Prognostics and Remaining Useful Life Prediction of Machinery:Advances,Opportunities,and Challenges

As the fundamental and key technique to ensure the safe and reliable operation of vital systems,prognostics with an emphasis on the remaining useful life(RUL)prediction has attracted great attention in the last decades.In this paper,we briefly discuss the general idea and advances of various prognostics and RUL prediction methods for machinery,mainly including data-driven methods,physics-based methods,hybrid methods,etc.Based on the observations fromthe state of the art,we provide comprehensive discussions on the possible opportunities and challenges of prognostics and RUL prediction of machinery so as to steer the future development.

Three-dimensional automatic artificial intelligence driven augmented-reality selective biopsy during nerve-sparing robot-assisted radical prostatectomy:A feasibility and accuracy study

Objective:To evaluate the accuracy of our new three-dimensional(3D)automatic augmented reality(AAR)system guided by artificial intelligence in the identification of tumour’s location at the level of the preserved neurovascular bundle(NVB)at the end of the extirpative phase of nerve-sparing robot-assisted radical prostatectomy.Methods:In this prospective study,we enrolled patients with prostate cancer(clinical stages cT1ce3,cN0,and cM0)with a positive index lesion at target biopsy,suspicious for capsular contact or extracapsular extension at preoperative multiparametric magnetic resonance imaging.Patients underwent robot-assisted radical prostatectomy at San Luigi Gonzaga Hospital(Orbassano,Turin,Italy),from December 2020 to December 2021.At the end of extirpative phase,thanks to our new AAR artificial intelligence driven system,the virtual prostate 3D model allowed to identify the tumour’s location at the level of the preserved NVB and to perform a selective excisional biopsy,sparing the remaining portion of the bundle.Perioperative and postoperative data were evaluated,especially focusing on the positive surgical margin(PSM)rates,potency,continence recovery,and biochemical recurrence.Results:Thirty-four patients were enrolled.In 15(44.1%)cases,the target lesion was in contact with the prostatic capsule at multiparametric magnetic resonance imaging(Wheeler grade L2)while in 19(55.9%)cases extracapsular extension was detected(Wheeler grade L3).3D AAR guided biopsies were negative in all pathological tumour stage 2(pT2)patients while they revealed the presence of cancer in 14 cases in the pT3 cohort(14/16;87.5%).PSM rates were 0%and 7.1%in the pathological stages pT2 and pT3(<3 mm,Gleason score 3),respectively.Conclusion:With the proposed 3D AAR system,it is possible to correctly identify the lesion’s location on the NVB in 87.5%of pT3 patients and perform a 3D-guided tailored nerve-sparing even in locally advanced diseases,without compromising the oncological safety in terms of PSM rates.

歪闪古建木构架整体纠偏方法与数值模拟

由于环境与人为等因素的长期影响,木结构古建筑普遍存在倾斜歪闪等损伤问题,严重影响了古木建筑的安全,亟需纠偏修复。研究尝试提出一种整体纠偏方法,构建木构架结构纠偏理论计算模型,通过数值模拟方法分析了纠偏过程的可行性,并以某多层木结构建筑的纠偏复位过程为例加以验证。结果表明:纠偏后结构楼层偏移明显减小,纠偏过程中主要结构构件仍然处于弹性范围内,纠偏效果良好,可为同类古建木构架纠偏理论研究提供借鉴。

国外建成遗产历史建筑信息模型(HBIM)前沿发展综述

当今,新兴数字技术对于文化遗产的保护与记录显得至关重要,相关技术的应用使得诸如降低文化遗产损坏风险、制定文化遗产预防性保护计划、实现文化遗产全生命周期记录与监管以及文化遗产可持续性保护等目标得以实现。作为文化遗产数字化保护领域的国际先进组织,国际建筑摄影测量与文化遗产记录委员会(CIPA Heritage Documentation)自1968年成立以来,一直积极致力于汇集与发表各类前沿的文化遗产保护与记录的研究成果和实践经验。CIPA2023会议是后疫情时代由该组织主办的首次线下集会,大会不仅为学术交流提供了平台,更汇集了大量前沿研究进展、创新的数据收集方法,以及应对复杂挑战时的有效解决方案。历史建筑信息模型(HBIM)是文化遗产数字化的核心和纽带。无论是对于单体历史建筑或建筑群,还是大规模考古遗址和景观遗产,抑或分布广泛的线性文化遗产,综合运用HBIM对其进行保护已被广泛认为是高效精准且潜力巨大的。本文通过检索国外学者在CIPA2023会议、国际摄影测量与遥感学会(ISPRS)出版物以及Web of Science(WoS)中所发表的HBIM研究文献,总结基于HBIM对遗产的复杂结构和构件进行建模,文化遗产管理、监测和修复的研究,可访问资源构建,以及探索数字孪生技术和深度学习的应用等四个方面的最新研究进展,介绍HBIM国际研究与应用的前沿进展。

Numerical study on local scour characteristics around submarine pipelines in the Yellow River Delta silty sandy soil under waves and currents

Due to their high reliability and cost-efficiency,submarine pipelines are widely used in offshore oil and gas resource engineering.Due to the interaction of waves,currents,seabed,and pipeline structures,the soil around submarine pipelines is prone to local scour,severely affecting their operational safety.With the Yellow River Delta as the research area and based on the renormalized group(RNG)k-εturbulence model and Stokes fifth-order wave theory,this study solves the Navier-Stokes(N-S)equation using the finite difference method.The volume of fluid(VOF)method is used to describe the fluid-free surface,and a threedimensional numerical model of currents and waves-submarine pipeline-silty sandy seabed is established.The rationality of the numerical model is verified using a self-built waveflow flume.On this basis,in this study,the local scour development and characteristics of submarine pipelines in the Yellow River Delta silty sandy seabed in the prototype environment are explored and the influence of the presence of pipelines on hydrodynamic features such as surrounding flow field,shear stress,and turbulence intensity is analyzed.The results indicate that(1)local scour around submarine pipelines can be divided into three stages:rapid scour,slow scour,and stable scour.The maximum scour depth occurs directly below the pipeline,and the shape of the scour pits is asymmetric.(2)As the water depth decreases and the pipeline suspension height increases,the scour becomes more intense.(3)When currents go through a pipeline,a clear stagnation point is formed in front of the pipeline,and the flow velocity is positively correlated with the depth of scour.This study can provide a valuable reference for the protection of submarine pipelines in this area.

从热力学计算到定形体系的实验表征设计全金属复合相变材料

用于热能管理的复合相变材料(C-PCMs)利用其一个或多个低熔点活性相的可逆相变(如熔化—凝固)存储和释放热能作为潜热。同时,高熔点的惰性相可以提供额外的性能,如定形性和改善的导热性。从难混溶合金中可获得具有这些特征的全金属复合材料体系。本文将热力学计算和实验测试相结合,探讨二元(Al-In,Al-Sn,Al-Bi和Cu-Bi)和三元(Al-In-Sn和Al-Bi-Sn)难混溶合金在100~300℃的温度范围内用作C-PCMs的潜力。结果表明,将这两种方法相结合对于全面理解复合体系和找到满足设计需求的最佳解决方案十分必要,它克服了“试错”法浪费时间的弊端,并为模拟提供了高质量的数据。

Topological optimization of ballistic protective structures through genetic algorithms in a vulnerability-driven environment

Reducing the vulnerability of a platform,i.e.,the risk of being affected by hostile objects,is of paramount importance in the design process of vehicles,especially aircraft.A simple and effective way to decrease vulnerability is to introduce protective structures to intercept and possibly stop threats.However,this type of solution can lead to a significant increase in weight,affecting the performance of the aircraft.For this reason,it is crucial to study possible solutions that allow reducing the vulnerability of the aircraft while containing the increase in structural weight.One possible strategy is to optimize the topology of protective solutions to find the optimal balance between vulnerability and the weight of the added structures.Among the many optimization techniques available in the literature for this purpose,multiobjective genetic algorithms stand out as promising tools.In this context,this work proposes the use of a in-house software for vulnerability calculation to guide the process of topology optimization through multi-objective genetic algorithms,aiming to simultaneously minimize the weight of protective structures and vulnerability.In addition to the use of the in-house software,which itself represents a novelty in the field of topology optimization of structures,the method incorporates a custom mutation function within the genetic algorithm,specifically developed using a graph-based approach to ensure the continuity of the generated structures.The tool developed for this work is capable of generating protections with optimized layouts considering two different types of impacting objects,namely bullets and fragments from detonating objects.The software outputs a set of non-dominated solutions describing different topologies that the user can choose from.

Adaptive multi-channel Bayesian graph attention network for IoT transaction security

With the rapid advancement of 5G technology,the Internet of Things(IoT)has entered a new phase of appli-cations and is rapidly becoming a significant force in promoting economic development.Due to the vast amounts of data created by numerous 5G IoT devices,the Ethereum platform has become a tool for the storage and sharing of IoT device data,thanks to its open and tamper-resistant characteristics.So,Ethereum account security is necessary for the Internet of Things to grow quickly and improve people's lives.By modeling Ethereum trans-action records as a transaction network,the account types are well identified by the Ethereum account classifi-cation system established based on Graph Neural Networks(GNNs).This work first investigates the Ethereum transaction network.Surprisingly,experimental metrics reveal that the Ethereum transaction network is neither optimal nor even satisfactory in terms of accurately representing transactions per account.This flaw may significantly impede the classification capability of GNNs,which is mostly governed by their attributes.This work proposes an Adaptive Multi-channel Bayesian Graph Attention Network(AMBGAT)for Ethereum account clas-sification to address this difficulty.AMBGAT uses attention to enhance node features,estimate graph topology that conforms to the ground truth,and efficiently extract node features pertinent to downstream tasks.An extensive experiment with actual Ethereum transaction data demonstrates that AMBGAT obtains competitive performance in the classification of Ethereum accounts while accurately estimating the graph topology.

高速动车组一系垂向半主动悬挂研究

轻量化是轨道交通车辆发展的重要方向,可降低车辆能耗和运营维护成本.然而车体轻量化改变了车体弹性模态频率,增大了车体结构振动,造成车辆垂向舒适性恶化.提出了一系垂向半主动悬挂策略,即采用可变阻尼减振器替换原有一系垂向减振器,通过对减振器阻尼特性进行实时控制,改善车体刚性和一阶弯曲模态振动.分析了车体刚性和弹性振动与构架振动的耦合关系,在此基础上对一系半主动悬挂的工作原理进行阐述.改进了经典的车辆垂向动力学模型,通过模型计算验证了车体和构架的多种耦合振动关系.对磁流变阻尼减振器的动态特性开展试验测试,建立了该减振器的动力学模型,实现对磁流变阻尼减振器非线性特性的准确预测.以国内某高速列车为原型,建立了完整的车辆动力学模型,并结合磁流变阻尼减振器动力学模型,对一系半主动悬挂的控制策略和应用效果展开研究,得到了两种易于工程应用的控制方法.结果表明一系半主动悬挂对车辆垂向振动,尤其是车体一阶弯曲振动具有显著的控制效果,可改善车辆垂向舒适性指标约30%.

Complementary memtransistors for neuromorphic computing: How, what and why

Memtransistors in which the source-drain channel conductance can be nonvolatilely manipulated through the gate signals have emerged as promising components for implementing neuromorphic computing.On the other side,it is known that the complementary metal-oxide-semiconductor(CMOS)field effect transistors have played the fundamental role in the modern integrated circuit technology.Therefore,will complementary memtransistors(CMT)also play such a role in the future neuromorphic circuits and chips?In this review,various types of materials and physical mechanisms for constructing CMT(how)are inspected with their merits and need-to-address challenges discussed.Then the unique properties(what)and poten-tial applications of CMT in different learning algorithms/scenarios of spiking neural networks(why)are reviewed,including super-vised rule,reinforcement one,dynamic vision with in-sensor computing,etc.Through exploiting the complementary structure-related novel functions,significant reduction of hardware consuming,enhancement of energy/efficiency ratio and other advan-tages have been gained,illustrating the alluring prospect of design technology co-optimization(DTCO)of CMT towards neuro-morphic computing.

A STAMP-Game model for accident analysis in oil and gas industry

Accidents in engineered systems are usually generated by complex socio-technical factors.It is beneficial to investigate the increasing complexity and coupling of these factors from the perspective of system safety.Based on system and control theories,System-Theoretic Accident Model and Processes(STAMP)is a widely recognized approach for accident analysis.In this paper,we propose a STAMP-Game model to analyze accidents in oil and gas storage and transportation systems.Stakeholders in accident analysis by STAMP can be regarded as players of a game.Game theory can,thus,be adopted in accident analysis to depict the competition and cooperation between stakeholders.Subsequently,we established a game model to study the strategies of both supervisory and supervised entities.The obtained results demonstrate that the proposed game model allows for identifying the effectiveness deficiency of the supervisory entity,and the safety and protection altitudes of the supervised entity.The STAMP-Game model can generate quantitative parameters for supporting the behavior and strategy selections of the supervisory and supervised entities.The quantitative data obtained can be used to guide the safety improvement,to reduce the costs of safety regulation violation and accident risk.

《威尼斯宪章》和《奈良真实性文件》对德国古迹保护影响的批判性反思

基于《威尼斯宪章》和《奈良真实性文件》,本文首先阐释了《威尼斯宪章》制定的意义及其历史背景,并分析其在德国历史背景中的应用。《威尼斯宪章》的诞生大约比德国古迹保护立法早10年,因此宪章对德国相关法律条文产生了深远影响。德国古迹保护机构对古迹历史性及其相关物质保护的态度也清晰地反映了这一影响。其次讨论了“真实性”一词的演变。该词最早出现在《威尼斯宪章》的序言中,随着《奈良真实性文件》以及《巴拉宪章》的发布,真实性在全球各种文化和传统中被重新定义。结合《保护世界文化和自然遗产公约》的发展,探讨制定《奈良真实性文件》的主要原因。最后,分析了《威尼斯宪章》和《奈良真实性文件》对当前德国古迹保护及相关立法所面临挑战的影响。

从《威尼斯宪章》-《奈良真实性文件》到当代问题

本文探讨了《威尼斯宪章》的诞生背景及其核心理念:一是避免重建,二是将保护范围扩展至历史地段。此举体现了对这些地段自身承载价值的重视,超越了仅作为古迹背景的局限性考量。其中,首项原则根植于传统真实性保护的辩论内容,而第二项原则则开创性地为建筑遗产的多元价值评估与潜力挖掘提供了新的视角。关于遗产真实性的辩论在奈良真实性会议达到了前所未有的高度。会议倡导了一种多元化的方法,旨在有效应对遗产保护中不断涌现的多维度挑战。这不仅响应了当代社会的迫切需求,更展现出对未来挑战的适应性与前瞻性。

Stochastic Maximum Principle for Optimal Advertising Models with Delay and Non-Convex Control Spaces

In this paper we study optimal advertising problems that model the introduction of a new product into the market in the presence of carryover effects of the advertisement and with memory effects in the level of goodwill. In particular, we let the dynamics of the product goodwill to depend on the past, and also on past advertising efforts. We treat the problem by means of the stochastic Pontryagin maximum principle, that here is considered for a class of problems where in the state equation either the state or the control depend on the past. Moreover the control acts on the martingale term and the space of controls U can be chosen to be non-convex but now the space of controls U can be chosen to be non-convex. The maximum principle is thus formulated using a first-order adjoint Backward Stochastic Differential Equations (BSDEs), which can be explicitly computed due to the specific characteristics of the model, and a second-order adjoint relation.

Boron Nitride-Integrated Lithium Batteries:Exploring Innovations in Longevity and Performance

The current global warming,coupled with the growing demand for energy in our daily lives,necessitates the development of more efficient and reliable energy storage devices.Lithium batteries(LBs)are at the forefront of emerging power sources addressing these challenges.Recent studies have shown that integrating hexagonal boron nitride(h-BN)nanomaterials into LBs enhances the safety,longevity,and electrochemical performance of all LB components,including electrodes,electrolytes,and separators,thereby suggesting their potential value in advancing eco-friendly energy solutions.This review provides an overview of the most recent applications of h-BN nanomaterials in LBs.It begins with an informative introduction to h-BN nanomaterials and their relevant properties in the context of LB applications.Subsequently,it addresses the challenges posed by h-BN and discusses existing strategies to overcome these limitations,offering valuable insights into the potential of BN nanomaterials.The review then proceeds to outline the functions of h-BN in LB components,emphasizing the molecular-level mechanisms responsible for performance improvements.Finally,the review concludes by presenting the current challenges and prospects of integrating h-BN nanomaterials into battery research.

Determination of the best materials for development and designing product using a multi-criteria decision-making

Purpose–Material selection,driven by wide and often conflicting objectives,is an important,sometimes difficult problem in material engineering.In this context,multi-criteria decision-making(MCDM)methodologies are effective.An approach of MCDM is needed to cater to criteria of material assortment simultaneously.More firms are now concerned about increasing their productivity using mathematical tools.To occupy a gap in the previous literature this research recommends an integrated MCDM and mathematical Bi-objective model for the selection of material.In addition,by using the Technique for Order Preference by Similarity to Ideal Solution(TOPSIS),the inherent ambiguities of decision-makers in paired evaluations are considered in this research.It goes on to construct a mathematical bi-objective model for determining the best item to purchase.Design/methodology/approach–The entropy perspective is implemented in this paper to evaluate the weight parameters,while the TOPSIS technique is used to determine the best and worst intermediate pipe materials for automotive exhaust system.The intermediate pipes are used to join the components of the exhaust systems.The materials usually used to manufacture intermediate pipe are SUS 436LM,SUS 430,SUS 304,SUS 436L,SUH 409 L,SUS 441 L and SUS 439L.These seven materials are evaluated based on tensile strength(TS),hardness(H),elongation(E),yield strength(YS)and cost(C).A hybrid methodology combining entropy-based criteria weighting,with the TOPSIS for alternative ranking,is pursued to identify the optimal design material for an engineered application in this paper.This study aims to help while filling the information gap in selecting the most suitable material for use in the exhaust intermediate pipes.After that,the authors searched for and considered eight materials and evaluated them on the following five criteria:(1)TS,(2)YS,(3)H,(4)E and(5)C.The first two criteria have been chosen because they can have a lot of influence on the behavior of the exhaust intermediate pipes,on their performance and on the cost.In this structure,the weights of the criteria are calculated objectively through the entropy method in order to have an unbiased assessment.This essentially measures the quantity of information each criterion contribution,indicating the relative importance of these criteria better.Subsequently,the materials were ranked using the TOPSIS method in terms of their relative performance by measuring each material from an ideal solution to determine the best alternative.The results show that SUS 309,SUS 432L and SUS 436 LM are the first three materials that the exhaust intermediate pipe optimal design should consider.Findings–The material matrix of the decision presented in Table 3 was normalized through Equation 5,as shown in Table 5,and the matrix was multiplied with weighting criteriaß_j.The obtained weighted normalized matrix V_ij is presented in Table 6.However,the ideal,worst and best value was ascertained by employing Equation 7.This study is based on the selection of material for the development of intermediate pipe using MCDM,and it involves four basic stages,i.e.method of translation criteria,screening process,method of ranking and search for methods.The selection was done through the TOPSIS method,and the criteria weight was obtained by the entropy method.The result showed that the top three materials are SUS 309,SUS 432L and SUS 436 LM,respectively.For the future work,it is suggested to select more alternatives and criteria.The comparison can also be done by using different MCDM techniques like and Choice Expressing Reality(ELECTRE),Decision-Making Trial and Evaluation Laboratory(DEMATEL)and Preference Ranking Organization Method for Enrichment Evaluation(PROMETHEE).Originality/value–The results provide important conclusions for material selection in this targeted application,verifying the employment of mutual entropy-TOPSIS methodology for a series of difficult engineering decisions in material engineering concepts that combine superior capacity with better performance as well as cost-efficiency in various engineering design.

Overview of Al-based nanoenergetic ingredients for solid rocket propulsion

The introduction of nano-sized energetic ingredients first occurred in Russia about 60 years ago and arose great expectations in the rocket propulsion community, thanks to the higher energy densities and faster energy release rates exhibited with respect to conventional ingredients. But, despite intense worldwide research programs, still today mostly laboratory level applications are reported and often for scientific purposes only. A number of practical reasons prevent the applications at industrial level: inert native coating of the energetic particles, nonuniform dispersion, aging, excessive viscosity of the slurry propellant, possible limitations in mechanical properties, more demanding safety issues, cost, and so on.This paper describes the main features in terms of performance of solid rocket propellants loaded with nanometals and intends to emphasize the unique properties or operating conditions made possible by the addition of the nano-sized energetic ingredients. Steady and unsteady combustion regimes are examined.