Cascading multi-segment rupture process of the 2023 Turkish earthquake doublet on a complex fault system revealed by teleseismic P wave back projection method

In this study,the vertical components of broadband teleseismic P wave data recorded by China Earthquake Network are used to image the rupture processes of the February 6th,2023 Turkish earthquake doublet via back projection analysis.Data in two frequency bands(0.5-2 Hz and 1-3 Hz)are used in the imaging processes.The results show that the rupture of the first event extends about 200 km to the northeast and about 150 km to the southwest,lasting~90 s in total.The southwestern rupture is triggered by the northeastern rupture,demonstrating a sequential bidirectional unilateral rupture pattern.The rupture of the second event extends approximately 80 km in both northeast and west directions,lasting~35 s in total and demonstrates a typical bilateral rupture feature.The cascading ruptures on both sides also reflect the occurrence of selective rupture behaviors on bifurcated faults.In addition,we observe super-shear ruptures on certain fault sections with relatively straight fault structures and sparse aftershocks.

Advancements in machine learning for material design and process optimization in the field of additive manufacturing

Additive manufacturing technology is highly regarded due to its advantages,such as high precision and the ability to address complex geometric challenges.However,the development of additive manufacturing process is constrained by issues like unclear fundamental principles,complex experimental cycles,and high costs.Machine learning,as a novel artificial intelligence technology,has the potential to deeply engage in the development of additive manufacturing process,assisting engineers in learning and developing new techniques.This paper provides a comprehensive overview of the research and applications of machine learning in the field of additive manufacturing,particularly in model design and process development.Firstly,it introduces the background and significance of machine learning-assisted design in additive manufacturing process.It then further delves into the application of machine learning in additive manufacturing,focusing on model design and process guidance.Finally,it concludes by summarizing and forecasting the development trends of machine learning technology in the field of additive manufacturing.

Flexible Fixture Design for the Top and End Surface Processing of NP2_NP4 Cylinder Heads

This paper focuses on the design of fixtures for NP2 and NP4 cylinder heads on a horizontal machining center of flexible machining automatic lines.It began with an analysis of the diagrams of part processing and working procedure which formed the basis for the design of the processing technology scheme,a selection of suitable machine tools,and the setting of processing parameters.Fixtures tailored to the chosen machine tools were then designed to meet the processing requirements.Additional aspects of the project included the design of part drawings,calculation of working time quota,design of auxiliary guides,support clamping,and hydraulic circuits,all aimed at fulfilling practical production requirements.

Process design and intensification of multicomponent azeotropes special distillation separation via molecular simulation and system optimization

This work provides an overview of distillation processes,including process design for different distillation processes,selection of entrainers for special distillation processes,system integration and intensification of distillation processes,optimization of process parameters for distillation processes and recent research progress in dynamic control strategies.Firstly,the feasibility of using thermodynamic topological theories such as residual curve,phase equilibrium line and distillation boundary line to analyze different separation regions is discussed,and the rationality of distillation process design is discussed by using its feasibility.Secondly,the application of molecular simulation methods such as molecular dynamics simulation and quantum chemical calculation in the screening of entrainer is discussed for the extractive distillation process.The thermal coupling mechanism of different distillation processes is used to explore the process of different process intensifications.Next,a mixed integer nonlinear optimization strategy for the distillation process based on different algorithms is introduced.Finally,the improvement of dynamic control strategies for different distillation processes in recent years is summarized.This work focuses on the application of process intensification and system optimization in the design of distillation process,and analyzes the challenges,prospects,and development trends of distillation technology in the separation of multicomponent azeotropes.

Study on trifluoromethanesulfonic acid-promoted synthesis of daidzein: Process optimization and reaction mechanism

Daidzein has been widely used in pharmaceuticals,nutraceuticals,cosmetics,feed additives,etc.Its preparation process and related reaction mechanism need to be further investigated.A cost-effective process for synthesizing daidzein was developed in this work.In this article,a two-step synthesis of daidzein(Friedel–Crafts acylation and[5+1]cyclization)was developed via the employment of trifluoromethanesulfonic acid(TfOH)as an effective promoting reagent.The effect of reaction conditions such as solvent,the amount of TfOH,reaction temperature,and reactant ratio on the conversion rate and the yield of the reaction,respectively,was systematically investigated,and daidzein was obtained in 74.0%isolated yield under optimal conditions.Due to the facilitating effect of TfOH,the Friedel–Crafts acylation was completed within 10 min at 90℃ and the[5+1]cyclization was completed within 180 min at 25℃.In addition,a possible reaction mechanism for this process was proposed.The results of the study may provide useful guidance for industrial production of daidzein on a large scale.

Combining reinforcement learning with mathematical programming:An approach for optimal design of heat exchanger networks

Heat integration is important for energy-saving in the process industry.It is linked to the persistently challenging task of optimal design of heat exchanger networks(HEN).Due to the inherent highly nonconvex nonlinear and combinatorial nature of the HEN problem,it is not easy to find solutions of high quality for large-scale problems.The reinforcement learning(RL)method,which learns strategies through ongoing exploration and exploitation,reveals advantages in such area.However,due to the complexity of the HEN design problem,the RL method for HEN should be dedicated and designed.A hybrid strategy combining RL with mathematical programming is proposed to take better advantage of both methods.An insightful state representation of the HEN structure as well as a customized reward function is introduced.A Q-learning algorithm is applied to update the HEN structure using theε-greedy strategy.Better results are obtained from three literature cases of different scales.

Process Characterization of the Transesterification of Rapeseed Oil to Biodiesel Using Design of Experiments and Infrared Spectroscopy

For optimization of production processes and product quality,often knowledge of the factors influencing the process outcome is compulsory.Thus,process analytical technology(PAT)that allows deeper insight into the process and results in a mathematical description of the process behavior as a simple function based on the most important process factors can help to achieve higher production efficiency and quality.The present study aims at characterizing a well-known industrial process,the transesterification reaction of rapeseed oil with methanol to produce fatty acid methyl esters(FAME)for usage as biodiesel in a continuous micro reactor set-up.To this end,a design of experiment approach is applied,where the effects of two process factors,the molar ratio and the total flow rate of the reactants,are investigated.The optimized process target response is the FAME mass fraction in the purified nonpolar phase of the product as a measure of reaction yield.The quantification is performed using attenuated total reflection infrared spectroscopy in combination with partial least squares regression.The data retrieved during the conduction of the DoE experimental plan were used for statistical analysis.A non-linear model indicating a synergistic interaction between the studied factors describes the reactor behavior with a high coefficient of determination(R^(2))of 0.9608.Thus,we applied a PAT approach to generate further insight into this established industrial process.

Inclusive Architecture:Digital Technologies,Co-design and Qualification of the Project Process

This article presents the scenario of programming use by architects and engineers,creating their own unique tools.The goal is to emulate and understand the phenomenon of Building Information Modeling(BIM)software customization by developing plug-ins that can explore the human-environment relationship.Demonstrate the process for building a plugin that seeks to equalize the theory of accessibility technical standards,visually impaired and architects.Use Design Science Research methodologies to guide the construction of artifacts for specific practical problems and the Collaborative Design/Co-design to understand and know the users’expertise.It is argued that the low quality of projects that include elements for the orientation of the visually impaired in Brazil is often related to an unstructured methodology in which important aspects such as the real needs of this group and the human-environment relationship are neglected.

A process monitoring method for autoregressive-dynamic inner total latent structure projection

As a dynamic projection to latent structures(PLS)method with a good output prediction ability,dynamic inner PLS(DiPLS)is widely used in the prediction of key performance indi-cators.However,due to the oblique decomposition of the input space by DiPLS,there are false alarms in the actual industrial process during fault detection.To address the above problems,a dynamic modeling method based on autoregressive-dynamic inner total PLS(AR-DiTPLS)is proposed.The method first uses the regression relation matrix to decompose the input space orthogonally,which reduces useless information for the predic-tion output in the quality-related dynamic subspace.Then,a vector autoregressive model(VAR)is constructed for the predic-tion score to separate dynamic information and static informa-tion.Based on the VAR model,appropriate statistical indicators are further constructed for online monitoring,which reduces the occurrence of false alarms.The effectiveness of the method is verified by a Tennessee-Eastman industrial simulation process and a three-phase flow system.

Multi-Criteria Wildfire Risk Hazard Assessment in GIS Environment: Projection for the Future and Impact on RES Projects Installation Planning

It is alarming for the fact that Wildfires number, severity and consequently impact have significantly increased during the last years, an aftermath of the Climate Change. One of the most affected areas worldwide is Mediterranean, due to the unique combination of its type of vegetation and demanding climatic conditions. This research is focused on the Region of Epirus in Greece, an area with significant natural vegetation and a range of geomorphological aspects. In order to estimate the Wildfire Risk Hazard, several factors have been used: geomorphological (slope, aspect, elevation, TWI, Hydrographic network), social (Settlements and landfils, roads, overhead lines and substations), environmental (land cover) and climatic (Fire Weather Index). Through a multi-criteria decision analysis (MCDA) and an analytic hierarchy process (AHP) in a GIS environment, the Wildfire Risk Hazard has been estimated not only for current conditions but also for future projections for the near future (2031-2060) and the far future (2071-2100). The selected case study includes the potential impact of the Wildfires to the installed (or targeted to be installed) RES projects in the studied region.

Integrated Project Library Exploration in Landscape Design Teaching for Environmental Design Majors

To enhance our talent cultivation model through“school-enterprise cooperation and industry-teaching fusion”,we aim to improve the“4321”Industry-Education Integration System.This includes actively promoting the use of case banks and project banks in teaching to develop students’practical engineering skills through hands-on application of professional knowledge.Additionally,landscape design courses emphasize practical learning experiences to implement the fundamental goal of“cultivating morality”.Guided by enhancing students’practical skills,we ensure alignment with course objectives and professional training requirements,emphasizing the seamless integration of theory and practice.

Review of Design of Process Parameters for Squeeze Casting

Squeeze casting(SC)is an advanced net manufacturing process with many advantages for which the quality and properties of the manufactured parts depend strongly on the process parameters.Unfortunately,a universal efficient method for the determination of optimal process parameters is still unavailable.In view of the shortcomings and development needs of the current research methods for the setting of SC process parameters,by consulting and analyzing the recent research literature on SC process parameters and using the CiteSpace literature analysis software,manual reading and statistical analysis,the current state and characteristics of the research methods used for the determination of SC process parameters are summarized.The literature data show that the number of pub-lications in the literature related to the design of SC process parameters generally trends upward albeit with signifi-cant fluctuations.Analysis of the research focus shows that both“mechanical properties”and“microstructure”are the two main subjects in the studies of SC process parameters.With regard to materials,aluminum alloys have been extensively studied.Five methods have been used to obtain SC process parameters:Physical experiments,numeri-cal simulation,modeling optimization,formula calculation,and the use of empirical values.Physical experiments are the main research methods.The main methods for designing SC process parameters are divided into three categories:Fully experimental methods,optimization methods that involve modeling based on experimental data,and theoreti-cal calculation methods that involve establishing an analytical formula.The research characteristics and shortcomings of each method were analyzed.Numerical simulations and model-based optimization have become the new required methods.Considering the development needs and data-driven trends of the SC process,suggestions for the develop-ment of SC process parameter research have been proposed.

Design Strategy of Digital Display Based on the Concept of Service Design

Based on the analysis of the concept,core,research content and method of service design,this paper explains the necessity of service design to participate in digital display,and further discusses how service design integrates with digital display,how to redesign the digital display system under the intervention of service design,and how to integrate user needs into it at all times.Finally,the design strategy of digital display under the concept of service design is proposed.

Design of Traditional Chinese Medicine Extraction Workshop Process and Automation System

Objective: This paper takes the example of a Panax notoginseng extraction workshop and designs an automated production workshop with advanced domestic capabilities. Methods: 1) Based on the small-scale Panax notoginseng extraction process, the feasibility of the workshop production process is demonstrated. 2) The workshop process design for Panax Notoginseng saponin extraction is completed, including production organization plans and the selection of key equipment. 3) For the Panax notoginseng extraction workshop process, an automated production control system is designed. Conclusion: Through optimized design of the production process and automation system, continuous and automated production of traditional Chinese medicine extraction is achieved, leading to improvements in drug quality and production efficiency.

A Comparative Analysis of Visualization Methods in Architecture:Employing Virtual Reality to Support the Decision-Making Process in the Architecture,Engineering,and Construction Industry

The design process of the built environment relies on the collaborative effort of all parties involved in the project.During the design phase,owners,end users,and their representatives are expected to make the most critical design and budgetary decisions-shaping the essential traits of the project,hence emerge the need and necessity to create and integrate mechanisms to support the decision-making process.Design decisions should not be based on assumptions,past experiences,or imagination.An example of the numerous problems that are a result of uninformed design decisions is“change orders”,known as the deviation from the original scope of work,which leads to an increase of the overall cost,and changes to the construction schedule of the project.The long-term aim of this inquiry is to understand the user’s behavior,and establish evidence-based control measures,which are actions and processes that can be implemented in practice to decrease the volume and frequency of the occurrence of change orders.The current study developed a foundation for further examination by proposing potential control measures,and testing their efficiency,such as integrating Virtual Reality(VR).The specific aim was to examine the effect of different visualization methods(i.e.,VR vs.construction drawings)on,(1)how well the subjects understand the information presented about the future/planned environment;(2)the subjects’perceived confidence in what the future environment will look like;(3)the likelihood of changing the built environment;(4)design review time;and(5)accuracy in reviewing and understanding the design.

ON DESIGN METHOD OF THE PRECISION CAM PROFILE WITH RANDOM PROCESSING ERRORS

Based on probability and statistic, a design method of precision cam profileconcerning the influence of random processing errors is advanced. Combining the design with theprocess, which can be used to predict that cam profiles will be successfully processed or not in thedesign stage, design of the cam can be done by balancing the economization and reliability. Inaddition, an fuzzy deduction method based on Bayers formula is advanced to estimate processingreasonable of the designed precision cam profile, and it take few samples.

The “Static” and “Dynamic” Design Verification Stages of the Lean Development Process: Automotive Industry

he design verification steps that take place in today’s automotive industry, which constitute the values of each successive or simultaneous phase in the new product development process, create a complex structure with the inclusion of each new technology and discipline. Therefore, step by step, each design verification phase definition in the flow contains important phase transition measurements or approval tolerances that ensure the simplicity and continuity of vehicle development processes. In addition, classification of design verification stages within the framework of this study or evaluation in two classes (static and dynamic) is a new approach, but it is a synthesis with the analysis of the new product development process. The vehicle’s basic structure, which constitutes the ergonomic and functional requirements of the vehicle in a static environment, takes into account the dynamic environment variables with crash or accident tests. Increasing new technology adaptations in the automotive industry have changed the new product development process that performs this function structurally and created the concept of design verification under consecutive or simultaneous process simplicity. From the autonomous driving to the use of alternative energy, possible accident scenarios and design verification phase transitions in the integration of parts and systems of the newly developed vehicle create a new structure that models and directs the lean product development process especially in the automotive industry in the coming days. In the lean product development process that takes place in the automotive industry, the design verification transition steps or the approval-control analysis of the development stages, which form a new and effective approach, are re-modeling the entire flow. Therefore, successful execution of design verification steps used in the control of new interdisciplinary product development phase transitions provides value creation.?Within the scope of this study, the effectiveness of the static and dynamic design verification steps, which are carried out in 5 global automotive companies included in the research, which constitute the stage transitions of the new product development process, has been measured. Apart from the design verification transition stages, the process variables that differ among the automotive companies involved in the research are excluded from the scope of this study. In other words, in field researches in the automotive industry, new vehicle design steps or basic engineering steps in the new product development process steps, while creating independent fixed variables, interdisciplinary collaborations, static and dynamic design verification transition stages they perform, or their sequence in the basic flow, is accepted as a dependent variable. Therefore, in the study, the positive effect of the automotive companies that included the static and dynamic design verification phase transition approvals in the lean product development process was investigated. Under the comparative analysis structure of the research, the effect of automotive companies, which accept international vehicle specifications as static design verification input, on market performance has been examined in depth. The detailed depth in the comparison analysis conducted under the second field studies of the study is due to the prediction of dynamic design verification stages to provide a high impact on the market performance, according to the static verification analysis. The new product development stages of the dependent variables were fixed and the flow-oriented?“effect”?of the independent variables in the basic process influenced by the design verification activities was analyzed under the new automotive industry company comparisons. In addition, the impact of the automotive design activities that make up the comparison analysis of the research on the scope of the lean product development stage and its effect on the basic process flow has been demonstrated competition-oriented. Therefore, sub-variables, options, criteria, results, which form a defined comparison problem, create basic test values that affect the problem.

Process design for gas condensate desulfurization and synthesis of nano-13X zeolite adsorbent: equilibrium and dynamic studies

This paper summarizes the results of a study of adsorption of sulfur compounds from a high-sulfur feed on improved spherical-shaped nano-AgX zeolite. For this purpose, the nano-AgX zeolite was initially synthesized and improved with silver compounds such as silver nitrate, and then it was utilized in the adsorption process. In order to investigate the equilibrium and dynamics of the adsorption process, adsorptive desulfurization of real feed(i.e., sour gas condensate from the South Pars gas field) was carried out in batch and continuous processes under several operating conditions; a temperature-dependent Langmuir isotherm model was used to fit the equilibrium data. The value of monolayer adsorption capacity(q_m) and adsorption enthalpy(ΔH) were calculated to be 1.044 mmol/g and 16.8 kJ/mol, respectively. Furthermore, a detailed theoretical model was employed in order to model the breakthrough experiments. The results revealed that an increase in the feed flow rate and 1/T values will cause linear and exponential increase in the total mass transfer coefficient(ks). Isotherm and dynamic breakthrough models were found to be in agreement with the experimental data.

Determination AHP Analysis of the Virtual Stage-Gate Process in the Global Scale Automotive Design

In this study, it is aimed to determine the ranking importance levels of the stages to be taken into consideration for new product development on a global scale in the automotive design process. New product design activity and stage-gate process differences between local automotive firms (serial production factory and stage-gate department in Turkey) and global automotive companies (serial production factory and stage-gate department in Turkey) are examined comparatively in the research area. In the automotive industry, which has been developing for a century, the question of how the local company products operating in the last sixty years have not been able to spread globally or how to develop global products is the background question of the research. For this purpose, one on one interviews were held with the managers of 3 national and 3 international automotive companies, who worked in the same region and who had previously designed a new vehicle, with design and product development departments.?According to?the data obtained by the AHP (Analytic Hierarchy Process) in the automotive design process, the importance of the criteria that should be taken into account for global product development has revealed. According to the results of the study, it was found that design validation stages were the most important globalization criterion in automotive design process as a new study area. In the comprehensive survey of the study, no other publication has been encountered to measure or evaluate the stages in the automotive design and new product development process in other sectors, including the vehicle industry. As in every industry sector, in the automotive industry, with the new product companies provide market development or competitive advantage. The new product is the life channel of a company and in the realization of this new vehicle;the disciplines of the automotive industry are formed by a hundred years of experience.

Sustainability Assessment and Ranking of Run of the River(RoR) Hydropower Projects Using Analytical Hierarchy Process(AHP):A Study from Western Himalayan Region of India

In the present scenario,tapping the unutilised hydropower potential is one of the highest priorities in developing countries of the world.Special emphasis is being imparted to run of the river(RoR)mode of power generation.However,the governments are now facing the dilemma whether to promote small hydropower projects(SHPs) or encourage large hydropower projects(LHPs).RoR large hydropower projects result into large scale cutting of mountains for constructing tunnels and access roads,generation of huge quantity of muck and large scale impact on flora and fauna due to diversion of rivers/streams.On the other hand,though SHPs are claimed to be greener and more sustainable by a section of researchers and energy planners but,they will be required to be set up in large number to generate equivalent amount of electricity.The aim of this study is to rank the most sustainable installed capacity range of RoR hydropower projects.To achieve this aim,the study proposes the use of quite popular multi-criteria decision making(MCDM)method of Operation Research named Analytical Hierarchy Process.A case study has been presented from Himachal Pradesh,a hydro rich state located in the western Himalayan region.As per sustainability assessment carried out in this study,hydropower projects in the capacity range 1 to 5 MW have been ranked to be the most sustainable.