Verification of Numerical Modeling in 2-D Wave Propagation in Rock

Compressional harmonic wave propagation from a cylindrical tunnel or borehole in an intact rock is the basis for investigation of the practical explosion waves in a fractured rock mass. The amplitudes of the radial stress wave obtained from the universal distinct element code (UDEC) were compared with the analytical solutions for two cases with different conditions. Good agreements between the UDEC results and the analytical solutions have been achieved. It indicates that UDEC can model 2-D dynamic problems at a high degree of accuracy.

Energy hub-based optimal planning for integrated energy systems considering part-load characteristics and synergistic effect of equipment

Integrated energy systems(lESs)represent a promising energy supply model within the energy internet.However,multi-energy flow coupling in the optimal configuration of IES results in a series of simplifications in the preliminary planning,affecting the cost,efficiency,and environmental performance of IES.A novel optimal planning method that considers the part-load characteristics and spatio-temporal synergistic effects of IES components is proposed to enable a rational design of the structure and size of IES.An extended energy hub model is introduced based on the“node of energy hub”concept by decomposing the IES into different types of energy equipment.Subsequently,a planning method is applied as a two-level optimization framework-the upper level is used to identify the type and size of the component,while the bottom level is used to optimize the operation strategy based on a typical day analysis method.The planning problem is solved using a two-stage evolutionary algorithm,combing the multiple-mutations adaptive genetic algorithm with an interior point optimization solver,to minimize the lifetime cost of the IES.Finally,the feasibility of the proposed planning method is demonstrated using a case study.The life cycle costs of the IES with and without consideration of the part-load characteristics of the components were$4.26 million and$4.15 million,respectively,in the case study.Moreover,ignoring the variation in component characteristics in the design stage resulted in an additional 11.57%expenditure due to an energy efficiency reduction under the off-design conditions.

Numerical simulation on rotordynamic characteristics of annular seal under uniform and non-uniform flows

Currently, the flow field of annular seals disturbed by the circular whirl motion of rotors is usually solved using computational fluid dynamics(CFD) to evaluate the five rotordynamic coefficients. The simulations are based on the traditional quasi-steady method. In this work, an improved quasi-steady method along with the transient method was presented to compute the rotordynamic coefficients of a long seal. By comparisons with experimental data, the shortcomings of quasi-steady methods have been identified. Then, the effects of non-uniform incoming flow on seal dynamic coefficients were studied by transient simulations. Results indicate that the long seal has large cross stiffness k and direct mass M which are not good for rotor stability, while the transient method is more suitable for the long seal for its excellent performance in predicting M. When the incoming flow is non-uniform, the stiffness coefficients vary with the eccentric directions. Based on the rotordynamic coefficients under uniform incoming flow, the linearized fluid force formulas, which can consider the effects of non-uniform incoming flow, have been presented and can well explain the varying-stiffness phenomenon.

Dynamics of firm size in healthcare industry

Healthcare is one of the world’s fastest growing industries consisting of broad services offered by various hospitals, physicians, nursing homes, diagnostic laboratories, pharmacies and supported by drugs, pharmaceuticals, chemicals, medical equipment, manufacturers and suppliers. The industry is highly fragmented, comprising of various ancillary sectors namely medical equipment and supplies, pharmaceutical, healthcare services, biotechnology, and alternative medicines. The present study focuses on the pharmaceutical and biotechnology segments of the healthcare industry, and presents a stochastic analysis of the evolution over time of firm size. A dynamic model is proposed that attempts to predict the evolutionary process of firm size distribution based on industry and product characteristics. A validation exercise, applying the model to pharmaceutical and the biotechnology industries finds that the predictions from the model are very close to the actual trajectories of firm size distributions within these industries at the global level. The results show interestingly, that the drivers of firm size dynamics are industry level characteristics that can be estimated from historical data with some accuracy. Specifically, it is found that firm size distributions are approaching a long-run equilibrium at a faster rate in the case of the pharmaceutical industry and that the dispersion of the distributions are shrinking over time above all for the biotechnology industry.

Industry dynamics in biotechnology

The field of modern biotechnology is thought to have largely begun in 1980, when the United States Supreme Court ruled that a genetically-modified microorganism could be patented. The growth of the Biotechnology industry has stimulated extensive research on its determinants. One of the areas which has attracted a fair amount of attention is the distribution of firm size within an industry. What is less known however, is the dynamics of firm size. This paper considers a statistical model to describe the spatial dynamics of firm size across the biotechnology industry. It is found that firm size fluctuates around its long run stationary equilibrium according to a temporal drift and random disturbance. The empirical results illustrate that diffusion is a potential technique for the analysis of spatial dynamics of firm size.

Extension of Direct Displacement-Based Design to Plan-Asymmetric RC Frame Buildings

The object of this paper is the evaluation of the seismic response of reinforced concrete frames designed according to the DDBD （direct displacement-based design） approach. The great part of research works about DDBD has been dedicated to planar frames, but recently also some proposals for 3D structures have been presented, in particular for wall structures. This paper will give a further contribution to the extension of the procedure for the case of plan-asymmetric RC （reinforced concrete） frames. The extended methodology is aimed at accounting for the floor rotations on the basis of a given lateral strength distribution along the plan. The procedure was applied to two plan-asymmetric RC frames, characterized by the same geometry but different lateral strength distributions along the plan. The seismic behavior of the designed frames was studied by adopting a fiber model and by performing pushover and nonlinear dynamic analyses.

FPGA Implementation of a Scalable and Highly Parallel Architecture for Restricted Boltzmann Machines

Restricted Boltzmann Machines (RBMs) are an effective model for machine learning;however, they require a significant amount of processing time. In this study, we propose a highly parallel, highly flexible architecture that combines small and completely parallel RBMs. This proposal addresses problems associated with calculation speed and exponential increases in circuit scale. We show that this architecture can optionally respond to the trade-offs between these two problems. Furthermore, our FPGA implementation performs at a 134 times processing speed up factor with respect to a conventional CPU.

Smarter eco-cities and their leading-edge artificial intelligence of things solutions for environmental sustainability:A comprehensive systematic review

The recent advancements made in the realms of Artificial Intelligence(AI)and Artificial Intelligence of Things(AIoT)have unveiled transformative prospects and opportunities to enhance and optimize the environmental performance and efficiency of smart cities.These strides have,in turn,impacted smart eco-cities,catalyzing ongoing improvements and driving solutions to address complex environmental challenges.This aligns with the visionary concept of smarter eco-cities,an emerging paradigm of urbanism characterized by the seamless integration of advanced technologies and environmental strategies.However,there remains a significant gap in thoroughly understanding this new paradigm and the intricate spectrum of its multifaceted underlying dimensions.To bridge this gap,this study provides a comprehensive systematic review of the burgeoning landscape of smarter eco-cities and their leadingedge AI and AIoT solutions for environmental sustainability.To ensure thoroughness,the study employs a unified evidence synthesis framework integrating aggregative,configurative,and narrative synthesis approaches.At the core of this study lie these subsequent research inquiries:What are the foundational underpinnings of emerging smarter eco-cities,and how do they intricately interrelate,particularly urbanism paradigms,environmental solutions,and data-driven technologies?What are the key drivers and enablers propelling the materialization of smarter eco-cities?What are the primary AI and AIoT solutions that can be harnessed in the development of smarter eco-cities?In what ways do AI and AIoT technologies contribute to fostering environmental sustainability practices,and what potential benefits and opportunities do they offer for smarter eco-cities?What challenges and barriers arise in the implementation of AI and AIoT solutions for the development of smarter eco-cities?The findings significantly deepen and broaden our understanding of both the significant potential of AI and AIoT technologies to enhance sustainable urban development practices,as well as the formidable nature of the challenges they pose.Beyond theoretical enrichment,these findings offer invaluable insights and new perspectives poised to empower policymakers,practitioners,and researchers to advance the integration of eco-urbanism and AI-and AIoT-driven urbanism.Through an insightful exploration of the contemporary urban landscape and the identification of successfully applied AI and AIoT solutions,stakeholders gain the necessary groundwork for making well-informed decisions,implementing effective strategies,and designing policies that prioritize environmental well-being.

Double Layer Composite Electrode Strategy for Efficient Perovskite Solar Cells with Excellent Reverse-Bias Stability

Perovskite solar cells(PSCs)have become the represent-atives of next generation of photovoltaics;nevertheless,their stability is insufficient for large scale deployment,particularly the reverse bias stability.Here,we propose a transparent conducting oxide(TCO)and low-cost metal composite electrode to improve the stability of PSCs without sacrificing the efficiency.The TCO can block ion migrations and chemical reactions between the metal and perovskite,while the metal greatly enhances the conductivity of the composite electrode.As a result,composite electrode-PSCs achieved a power conversion efficiency(PCE)of 23.7%(certified 23.2%)and exhibited excellent stability,maintaining 95%of the initial PCE when applying a reverse bias of 4.0 V for 60 s and over 92%of the initial PCE after 1000 h continuous light soaking.This composite electrode strategy can be extended to different combinations of TCOs and metals.It opens a new avenue for improving the stability of PSCs.

The synergistic interplay of artificial intelligence and digital twin in environmentally planning sustainable smart cities:A comprehensive systematic review

The dynamic landscape of sustainable smart cities is witnessing a significant transformation due to the integration of emerging computational technologies and innovative models.These advancements are reshaping data-driven planning strategies,practices,and approaches,thereby facilitating the achievement of environmental sustainability goals.This transformative wave signals a fundamental shift d marked by the synergistic operation of artificial intelligence(AI),artificial intelligence of things(AIoT),and urban digital twin(UDT)technologies.While previous research has largely explored urban AI,urban AIoT,and UDT in isolation,a significant knowledge gap exists regarding their synergistic interplay,collaborative integration,and collective impact on data-driven environmental planning in the dynamic context of sustainable smart cities.To address this gap,this study conducts a comprehensive systematic review to uncover the intricate interactions among these interconnected technologies,models,and domains while elucidating the nuanced dynamics and untapped synergies in the complex ecosystem of sustainable smart cities.Central to this study are four guiding research questions:1.What theoretical and practical foundations underpin the convergence of AI,AIoT,UDT,data-driven planning,and environmental sustainability in sustainable smart cities,and how can these components be synthesized into a novel comprehensive framework?2.How does integrating AI and AIoT reshape the landscape of datadriven planning to improve the environmental performance of sustainable smart cities?3.How can AI and AIoT augment the capabilities of UDT to enhance data-driven environmental planning processes in sustainable smart cities?4.What challenges and barriers arise in integrating and implementing AI,AIoT,and UDT in data-driven environmental urban planning,and what strategies can be devised to surmount or mitigate them?Methodologically,this study involves a rigorous analysis and synthesis of studies published between January 2019 and December 2023,comprising an extensive body of literature totaling 185 studies.The findings of this study surpass mere interdisciplinary theoretical enrichment,offering valuable insights into the transformative potential of integrating AI,AIoT,and UDT technologies to advance sustainable urban development practices.By enhancing data-driven environmental planning processes,these integrated technologies and models offer innovative solutions to address complex environmental challenges.However,this endeavor is fraught with formidable challenges and complexities that require careful navigation and mitigation to achieve desired outcomes.This study serves as a comprehensive reference guide,spurring groundbreaking research endeavors,stimulating practical implementations,informing strategic initiatives,and shaping policy formulations in sustainable urban development.These insights have profound implications for researchers,practitioners,and policymakers,providing a roadmap for fostering resiliently designed,technologically advanced,and environmentally conscious urban environments.

Energy Planning of Beijing Towards Low-carbon,Clean and Efficient Development in 2035

Energy transition towards clean,efficient energy supply has been a common sense of the government and public in China.However,lacking reasonable planning will lead to undisciplined development,resource waste,and excessive investment.In this context,this paper investigates potential pathways of Beijing energy transition towards a high-level low-carbon,clean and efficient energy system in 2035 with an extended energysocpe model.Firstly,based on available data,future energy demands are predicted by a newly proposed hybrid forecasting method,which combines the traditional regression model,grey model,and support vector machine model with an entropy-based weighted factor.Secondly,the superstructure-based optimization model is employed to investigate the system configuration and operation strategy of the future Beijing energy system.Finally,the uncertainty impact of electricity price,natural gas price,hydrogen price,and the capital expenditures of electrolyzer and steam methane reforming for hydrogen applications are studied.The forecasting results show that all walks of life will witness a continuously increasing energy demand in multiple sectors of Beijing towards 2035.The planning results suggest that the imported electricity and natural gas will dominate the energy supply of Beijing in 2035 with a contribution of 86%of the energy resources consumption of 384 TWh.Moreover,the energy system presents a high end-use electrification level of 65%and high penetration of efficient technologies,which supply 119 TWh via combined heat and power,26 TWh via heat pump and 95 TWh via district heating network.The energy use of various sectors of energy resources,technologies and end-use are closely related.Hydrogen will have an increased penetration in the private mobility sector,but the locally generated hydrogen is mainly from steam methane reforming technology.

隧道压力拱与围岩变形关系

压力拱是隧道工程开挖后围岩的自承载现象,对隧道稳定有着重要意义。通过数值分析可以发现,压力拱拱体内的岩体变形增长缓慢,压力拱内边界与隧道之间的岩体变形急剧增加;压力拱内边界越靠近隧道,隧道的变形量越小;压力拱厚度小,外边界处的变形也相对较小。在节理倾角分别为30°和60°及不同的节理间距条件下,压力拱位置、形态及拱体厚度均有所变化。

围岩自调节成拱特性的实验与数值分析

本文在围岩应力分析的基础上,通过物理实验模拟和数值计算,分析了由于隧道开挖后应力变化引起的围岩自调节成拱的特性及相关影响因素作用下的压力拱成拱规律。在本文中,将压力拱内边界距洞口的距离和拱体厚度作为判定压力拱成拱和评价围岩稳定的参数。当内边界靠近隧道洞口,围岩基本稳定;压力拱的厚度小意味着需要较少的岩体来承担拱体自身和其上岩体的荷载。在此基础上,运用平面应变相似模拟实验模拟隧道开挖过程,对开挖过程中洞口周围应力升高区进行了观察和分析,明确了压力拱的成拱,以及随着距离洞口越近变形增加的幅度越大等现象。运用数值分析发现,随着节理的间距的减小,压力拱内边界靠近洞口,压力拱厚度增大;在2组节理围岩中,节理倾角分别为30°和60°时,成拱最不利;而节理的黏结强度对压力拱成拱的影响程度与节理摩擦角的大小相关联,摩擦角大于20°时,节理黏结强度对压力拱成拱影响甚微。

山区公路隧道建设灾害预防与控制技术

以典型山区公路隧道为工程背景,对山区公路隧道在开挖施工、建设过程中所遇到的工程灾害问题进行了系统研究,并对此进行了概述.主要包括4个方面:①建立了公路隧道围岩分级的距离判别分析模型;②研制了能模拟深埋隧道围岩受力情况的组合加载装置,并利用突变理论对洞室屈曲岩爆的发生机理进行了研究;③利用有限差分软件FLAC3D,对富水地段公路隧道进行三维流固耦合分析,在此基础上提出了包括粘贴式集排水系统在内的一系列针对性很强的渗漏水控制技术,并成功地在常吉高速公路相关隧道顺利实施;④提出了推断岩土力学参数概率密度函数的新方法,并对隧道衬砌可靠度进行了相关分析.这些研究内容各自独立又紧密联系,能够在一定程度上对隧道的安全施工和长效运营提供系统的技术保障.

Science Missions Using CubeSats

As the role of missions and experiments carried out in outer space becomes more and more essential in our understanding of many earthly problems,such as resource management,environmental problems,and disaster management,as well as space science questions,thanks to their lower cost and faster development process CubeSats can benefit humanity and therefore,young scientists and engineers have been motivated to research and develop new CubeSat missions.Not very long after their inception,CubeSats have evolved to become accepted platforms for scientific and commercial applications.The last couple of years showed that they are a feasible tool for conducting scientific experiments,not only in the Earth orbit but also in the interplanetary space.For many countries,a CubeSat mission could prompt the community and young teams around the world to build the national capacity to launch and operate national space missions.This paper presents an overview of the key scientific and engineering gateways opened up to the younger scientific community by the advent and adaptation of new technology into CubeSat missions.The role of cooperation and the opportunities for capacity-building and education are also explored.Thus,the present article also aims to provide useful recommendations to scientists,early-career researchers,engineers,students,and anyone who intends to explore the potential and opportunities offered by CubeSats and CubeSats-based missions.

Swirl Jets in Crossflow at Low Velocity Ratios

This investigation examines experimentally the behavior of swirled jets produced by axial flow fans blowing into a crossflow at low velocity ratios. The main difference with non-swirl cases is an asymmetry of the dominant kidney vortex and a slight distortion of the jet trace downstream of the injection hole. The effect of jet rotation at relatively low swirl numbers and similar velocity ratios is also investigated by a validated computational analysis tool. The numerical results are analyzed by means of various post-processing procedures, aiming to clarify, quantify and analyze the impact of swirl on the characteristics and the flow domain of a jet in crossflow. In general, swirl introduces an asymmetry in all examined quantities and prevents the penetration of the jet into the crossflow, causing the jet to remain closer to the wall surface. The rotation of the injected fluid results in an imparity of the two parts of the Counter Rotating Vortex Pair （CVP） which is no longer symmetric to the axial centerline plane. High swirl numbers result in the destruction of the CVP and the dominant kidney shape vortex is transformed into a comma shape vortex, rotating close to the wall.

Universe and Matter Conjectured as a 3-Dimensional Lattice with Topological Singularities

One fundamental problem of modern physics is the search for a theory of everything able to explain the nature of space-time, what matter is and how matter interacts. There are various propositions, as Grand Unified Theory, Quantum Gravity, Supersymmetry, String and Superstring Theories, and M-Theory. However, none of them is able to consistently explain at the present and same time electromagnetism, relativity, gravitation, quantum physics and observed elementary particles. In this paper, one summarizes the content of a new book, published in English [2] and in French [3], in which it is suggested that Universe could be a massive elastic 3D-lattice, and that fundamental building blocks of Ordinary Matter could consist of topological singularities of this lattice, namely diverse dislocation loops and disclination loops. For an isotropic elastic lattice obeying Newton’s law, with specific assumptions on its elastic properties, one obtains the result that the behaviours of this lattice and of its topological defects display “all” known physics, unifying electromagnetism, relativity, gravitation and quantum physics, and resolving some longstanding questions of modern cosmology. Moreover, studying lattices with axial symmetries, represented by “colored” cubic 3D-lattices, one has identified a lattice structure whose topological defect loops coincide with the complex zoology of elementary particles, which could open a very promising field of research. Here, only main steps and principal results of the new theory are presented and discussed, without showing the mathematical concepts and developments contained in the book.

Study on the Reversible DC-DC Converter as Interface between Low and Medium Voltage DC Networks

This paper introduces an isolated reversible DC-DC converter with a particular topology, which benefits from both the NPC （neutral point clamped） structure and the series-parallel connection of converters. The key property of the proposed topology is the output voltage elevation above the blocking capabilities of each switch, without taking to a delicate synchronization of series-connected semiconductors. The converter is composed by two identical cells, each containing a full bridge, a medium frequency transformer and an NPC converter, connected in parallel at the input and in series at the output. The operation principle of each cell, into which a trapezoidal modulation was implemented, is similar to a DAB （dual active bridge）. A new model improves the dynamic performance of the controller. Simulation and experimental results verify the proposed topology, its control and start-up strategy.

Weight and Efficiency Optimized DC/DC Converter Based on Multiple Interleaved Channels

Today, energy saving is one of the main objectives for engineers. In the case of mobile applications, energy can be saved by two different ways： decreasing the total masse of the system and increasing the efficiency of the overall system. This paper presents two optimization strategies to design a predefined multichannel structure of a boost converter which is dedicated to a solar airplane and used to interface PV panels and the battery system. The first strategy is a multi-criterion method that is able to trace the dependency between the converter＇s efficiency and its power density through the intermediary of the Pareto front. The second method, a mono-criterion approach, maximizes efficiency while respecting the constraint imposed on power density. The mono-criterion method that is applied to maximizing the European efficiency criterion showed that an increase in the number of channels enhanced the quantity of energy collected over a day by increasing the power density of the converter. At the end of the paper, the optimal design calculated was built to give an example of the result obtained by this design methodology. The results of the efficiency measurements made on a realized prototype are presented in this paper.

Emerging role of machine learning in light-matter interaction

Machine learning has provided a huge wave of innovation in multiple fields,including computer vision,medical diagnosis,life sciences,molecular design,and instrumental development.This perspective focuses on the implementation of machine learning in dealing with light-matter interaction,which governs those fields involving materials discovery,optical characterizations,and photonics technologies.We highlight the role of machine learning in accelerating technology development and boosting scientific innovation in the aforementioned aspects.We provide future directions for advanced computing techniques via multidisciplinary efforts that can help to transform optical materials into imaging probes,information carriers and photonics devices.