Systems Engineering Research Articles

Numerical study on the behavior of a polymeric MHD nanofluid: entropy optimization and thermal analysis

PurposeAnalyzing and reducing entropy generation is useful for enhancing the thermodynamic performance of engineering systems. This study aims to explore how polymers and nanoparticles in the presence of Lorentz forces influence the fluid behavior and heat transfer characteristics to lessen energy loss and entropy generation.Design/methodology/approachThe dispersion model is initially used to examine the behavior of polymer additives over a magnetized surface. The governing system of partial differential equations (PDEs) is subsequently reduced through the utilization of similarity transformation techniques. Entropy analysis is primarily performed through the implementation of numerical computations on a non-Newtonian polymeric FENE-P model.FindingsThe numerical simulations conducted in the presence of Lorentz forces provide significant insights into the consequences of adding polymers to the base fluid. The findings suggest that such an approach minimizes entropy in the flow region. Through the utilization of polymer-MHD (magnetohydrodynamic) interactions, it is feasible to reduce energy loss and improve the efficiency of the system.Originality/valueThis study’s primary motivation and novelty lie in examining the significance of polymer additives as agents that reduce entropy generation on a magnetic surface. The author looks at how nanofluids affect the development of entropy and the loss of irreversibility. To do this, the author uses the Lorentz force, the Soret effect and the Dufour effect to minimize entropy. The findings contribute to fluid mechanics and thermodynamics by providing valuable insights for engineering systems to increase energy efficiency and conserve resources.

High oxidation state on porous Ga-Ag9In4 catalyst enhance CO2 electroreduction to CO

The oxidation state of Ga, In and Ag active sites for the selective electrochemical conversion of CO2 to CO has been successfully modulated through the construction of a porous Ga-Ag9In4 liquid alloy catalyst. X-ray photoelectron spectroscopy measurements confirmed the formation of a higher amount of oxidized states on the high-performing Ga-Ag9In4 electrode surface during the CO2 reduction reaction process. Based on density functional theory calculations, the Ga-Ag9In4 catalyst with a high oxidized species exhibits an electronic-rich surface that promotes CO2 adsorption and activation. In a H-type electrolysis cell, the porous Ga-Ag9In4 catalyst exhibits a maximum Faradaic efficiency of 88 % for CO production, with current densities of 30.2 mA·cm−2. This strategy of porous liquid alloy engineering and oxidation state modulation in multicomponent systems has good application prospect and research value for enhancing electrocatalytic performance.

Rational Engineering of Cytosolic Delivery Systems for Protein Therapeutics

Rational Engineering of Cytosolic Delivery Systems for Protein Therapeutics

Deciphering domain structures of Aspergillus and Streptomyces GH3-β-Glucosidases: a screening system for enzyme engineering and biotechnological applications

The glycoside hydrolase family 3 (GH3) β-glucosidases from filamentous fungi are crucial industrial enzymes facilitating the complete degradation of lignocellulose, by converting cello-oligosaccharides and cellobiose into glucose. Understanding the diverse domain organization is essential for elucidating their biological roles and potential biotechnological applications. This research delves into the variability of domain organization within GH3 β-glucosidases. Two distinct configurations were identified in fungal GH3 β-glucosidases, one comprising solely the GH3 catalytic domain, and another incorporating the GH3 domain with a C-terminal fibronectin type III (Fn3) domain. Notably, Streptomyces filamentous bacteria showcased a separate clade of GH3 proteins linking the GH3 domain to a carbohydrate binding module from family 2 (CBM2). As a first step to be able to explore the role of accessory domains in β-glucosidase activity, a screening system utilizing the well-characterised Aspergillus niger β-glucosidase gene (bglA) in bglA deletion mutant host was developed. Based on this screening system, reintroducing the native GH3-Fn3 gene successfully expressed the gene allowing detection of the protein using different enzymatic assays. Further investigation into the role of the accessory domains in GH3 family proteins, including those from Streptomyces, will be required to design improved chimeric β-glucosidases enzymes for industrial application.

Improving surveillance of emergency department activity through natural language processing

Objective and ApproachManagers, clinicians and policymakers have limited information on near-real time patterns of attendance at emergency departments (ED). Our aim was to develop a surveillance system through extracting information from the presenting complaint to develop and feed activity dashboards, improve injury surveillance and support research. We developed a Natural Language Processing (NLP) pipeline using the General Architecture for Text Engineering (GATE) system. The pipeline produced Unified Medical Language System (UMLS) codes from ED presenting complaint records and also implemented the Joint Action on Monitoring Injuries in Europe (JAMIE) Minimum Dataset. We classified complaints into 31 common problem presentations (Coughs, Bleeds, Mental Health, Dizziness...), along with categories from JAMIE (Mechanism of Injury, Location, Activity, Intent…). ResultsPreliminary results are from a pilot study of 86,416 presenting complaints from Morriston Hospital in 2014. The most common terms used for grouped symptoms/categories were “Injury” (38.6%, n=28691), “Pain” (22.8%, n=19420), “Unwell” (7.2%, n=6117), “Bleeding” (6.7%, n=5760), and “Shortness of Breath” (3.8%, n=3255). 32.3% of records contained Mechanism of Injury codes, including, falls (15.2%, n=13174), struck by/against (6.9%, n=5960), cuts (5.6%, n=4833), road traffic collisions (2.5%, n=2124) and poisoning (1%, n=900). We are continuing to refine and validate the categories using precision and recall and with comparison with coded diagnoses. Conclusions and Implications NLP can be used to extract valuable additional detailed information from ED data. We will further develop the algorithms for all hospitals in Wales for data from 2023 and design dashboards to produce a near-real time surveillance system.

Using Systems Engineering and Implementation Science to Design an Implementation Package for Preoperative Comprehensive Geriatric Assessment Among Older Adults Having Major Abdominal Surgery: Protocol for a 3-Phase Study.

Older Americans, a growing segment of the population, have an increasing need for surgical services, and they experience a disproportionate burden of postoperative complications compared to their younger counterparts. A preoperative comprehensive geriatric assessment (pCGA) is recommended to reduce risk and improve surgical care delivery for this population, which has been identified as vulnerable. The pCGA optimizes multiple chronic conditions and factors commonly overlooked in routine preoperative planning, including physical function, polypharmacy, nutrition, cognition, mental health, and social and environmental support. The pCGA has been shown to decrease postoperative morbidity, mortality, and length of stay in a variety of surgical specialties. Although national guidelines recommend the use of the pCGA, a paucity of strategic guidance for implementation limits its uptake to a few academic medical centers. By applying implementation science and human factors engineering methods, this study will provide the necessary evidence to optimize the implementation of the pCGA in a variety of health care settings. The purpose of this paper is to describe the study protocol to design an adaptable, user-centered pCGA implementation package for use among older adults before major abdominal surgery. This protocol uses systems engineering methods to develop, tailor, and pilot-test a user-centered pCGA implementation package, which can be adapted to community-based hospitals in preparation for a multisite implementation trial. The protocol is based upon the National Institutes of Health Stage Model for Behavioral Intervention Development and aligns with the goal to develop behavioral interventions with an eye to real-world implementation. In phase 1, we will use observation and interviews to map the pCGA process and identify system-based barriers and facilitators to its use among older adults undergoing major abdominal surgery. In phase 2, we will apply user-centered design methods, engaging health care providers, patients, and caregivers to co-design a pCGA implementation package. This package will be applicable to a diverse population of older patients undergoing major abdominal surgery at a large academic hospital and an affiliate community site. In phase 3, we will pilot-test and refine the pCGA implementation package in preparation for a future randomized controlled implementation-effectiveness trial. We anticipate that this study will take approximately 60 months (April 2023-March 2028). This study protocol will generate (1) a detailed process map of the pCGA; (2) an adaptable, user-centered pCGA implementation package ready for feasibility testing in a pilot trial; and (3) preliminary pilot data on the implementation and effectiveness of the package. We anticipate that these data will serve as the basis for future multisite hybrid implementation-effectiveness clinical trials of the pCGA in older adults undergoing major abdominal surgery. The expected results of this study will contribute to improving perioperative care processes for older adults before major abdominal surgery. DERR1-10.2196/59428.

Synthetic redesign of Escherichia coli W for faster metabolism of sugarcane molasses

BackgroundSugarcane molasses, rich in sucrose, glucose, and fructose, offers a promising carbon source for industrial fermentation due to its abundance and low cost. However, challenges arise from the simultaneous utilization of multiple sugars and carbon catabolite repression (CCR). Despite its nutritional content, sucrose metabolism in Escherichia coli, except for W strain, remains poorly understood, hindering its use in microbial fermentation. In this study, E. coli W was engineered to enhance sugar consumption rates and overcome CCR. This was achieved through the integration of a synthetically designed csc operon and the optimization of glucose and fructose co-utilization pathways. These advancements facilitate efficient utilization of sugarcane molasses for the production of 3-hydroxypropionic acid (3-HP), contributing to sustainable biochemical production processes.ResultsIn this study, we addressed challenges associated with sugar metabolism in E. coli W, focusing on enhancing sucrose consumption and improving glucose-fructose co-utilization. Through targeted engineering of the sucrose utilization system, we achieved accelerated sucrose consumption rates by modulating the expression of the csc operon components, cscB, cscK, cscA, and cscR. Our findings revealed that monocistronic expression of the csc genes with the deletion of cscR, led to optimal sucrose utilization without significant growth burden. Furthermore, we successfully alleviated fructose catabolite repression by modulating the binding dynamics of FruR with the fructose PTS regulon, enabling near-equivalent co-utilization of glucose and fructose. To validate the industrial applicability of our engineered strain, we pursued 3-HP production from sugarcane molasses. By integrating heterologous genes and optimizing metabolic pathways, we achieved improvements in 3-HP titers compared to previous studies. Additionally, glyceraldehyde-3-phosphate dehydrogenase (gapA) repression aids in carbon flux redistribution, enhancing molasses conversion to 3-HP.ConclusionsDespite limitations in sucrose metabolism, the redesigned E. coli W strain, adept at utilizing sugarcane molasses, is a valuable asset for industrial fermentation. Its synthetic csc operon enhances sucrose consumption, while mitigating CCR improves glucose-fructose co-utilization. These enhancements, coupled with repression of gapA, aim to efficiently convert sugarcane molasses into 3-HP, addressing limitations in sucrose and fructose metabolism for industrial applications.

Examination of AI Enhanced Distributed Systems and its Effects on Software Engineering

Distributed systems are groups of independent computers that appear to the system's users as a single coherent system. These systems involve several critical factors, including network communication, concurrency, and fault tolerance, which are vital in software engineering. For example, cloud computing platforms like Amazon Web Services (AWS) use distributed systems to offer scalable, on-demand resources to millions of users worldwide. The introduction of Artificial Intelligence (AI) into software engineering marks a transformative period that reshapes traditional development processes and breaks down the complexity of distributed systems. AI automates routine tasks and simplifies complex processes, serving as a digital collaborator that enables developers to focus on strategic thinking and creativity. One significant advantage of using AI in distributed systems within software engineering is enhanced resource optimization. AI can identify irregularities that might indicate hardware malfunctions and take preventative measures to address them, such as rerouting traffic to healthier servers. However, distributed systems also have challenges, including increased complexity in system design, difficulty ensuring data consistency, and potential security vulnerabilities. The intricate structure of these systems can result in problems with high startup costs, safety risks, and the accuracy of the data provided. Integrating AI into distributed systems offers both significant advantages and disadvantages. This study evaluates how AI impacts the efficiency and security of distributed systems in software engineering. By analyzing the advantages and disadvantages of AI-enhanced distributed systems, we can gain a comprehensive understanding of their overall effectiveness and implications in the field.

Understanding the Variety of Domain Models: Views, Programs, Animations, and Other Models

Humanity has long since used models, in different shapes and forms, to understand, redesign, communicate about, and shape, the world around us; including many different social, economic, biological, chemical, physical, and digital aspects. This has resulted in a wide range of modeling practices. When the models as used in such modeling practices have a key role to play in the activities in which these practices are ‘embedded’, the need emerges to consider the effectiveness and efficiency of such processes, and speak about modeling capabilities. In the latter situation, it also becomes relevant to develop a thorough understanding of the artifacts involved in modeling practices/capabilities. One context in which models play (an increasingly) important role is model-driven systems development, including software engineering, information systems engineering, business process engineering, enterprise engineering, and enterprise architecture management. In such a context, we come across a rich variety of modeling related artifacts, such as views, diagrams, programs, animations, specifications, etc. In this paper, which is actually part of an ongoing ‘journey’ in which we aim to gain deeper insights into the foundations of modeling, we take a fundamental look at the variety of modeling related artifacts as used in the context of model-driven (systems) development, while also presenting an associated framework for understanding, synthesizing the insights we obtained during the ‘journey’ so-far. In doing so, we will also argue that the aforementioned artifacts are actually specific kinds of models, albeit for fundamentally different purposes. The provided framework for understanding involves definitions of domain model, the Return on Modeling Effort (RoME), the conceptual fidelity of domain models, as well as views as a mechanism to manage the complexity of domain models.

Method for Developing the System Architecture of Existing Industrial Objects for Digital Representation Tasks

This paper presents a method for creating the system architecture of existing industrial objects based on Model-Based Systems Engineering (MBSE) principles. The method aims to form a digital representation of physical objects, which is crucial in the digital transformation of industrial enterprises. It allows for the accurate reflection of all components, processes, functions, and interrelationships within an object. The methodology includes stages of data collection, structuring, development of ontological models, and the integration of a comprehensive system architecture into the digital space. This method was tested using a small hydroelectric power plant, revealing its key advantages and disadvantages and identifying areas for further improvement. The main findings indicate a significant improvement in understanding the system architecture for scenario modeling and digital operation of the objects. Despite challenges such as the need for multiple iterations and high data requirements, the methodology demonstrates the potential for applying MBSE in the digital transformation of existing industrial objects.

Terminological features of the concept of signal-to-noise ratio when processing ultra-wideband signals

Currently, when processing various signals and studying various types of receivers, there are many definitions for one of the basic characteristics of radio systems – signal-to-noise ratio (SNR). At the same time, the terminological feature of the SNR concept is that any definition within the framework of a locally solvable signal processing problem is correct. However, difficulties arise when comparing the effectiveness of one algorithm with another, when studying different signal models, or when measuring the SNR in different parts of the receiving system. Some researchers ignore this fact due to the apparent absolute clarity of this issue, which leads to incorrect comparison of various processing algorithms or the formation of obviously unrealizable requirements for the designed equipment. In each locally solved problem, the determination of SNR will be individual, and comparison of efficiency at a fixed SNR must be carried out with mandatory scaling of signal energies depending on the formulation of the problem. This paper systematizes the terminological features of the SNR concept in order to ensure uniformity of its application by researchers and engineers. The purpose of the work is to systematize the definition of SNR for various signal models and conditions for measuring this characteristic, to specify the results in terms of terminological features of UWB signal processing and to propose a model for recalculating the SNR depending on the stage of the signal transmission and reception process. The paper examines the determination of SNR at the input and output of optimal and matched filters, at the output of optimal receivers operating under conditions of various a priori uncertainties, as well as when processing various classes of signals. By determining the SNR at the output of the matched filter and the SNR at the output of the maximum likelihood receiver for a rectangular video pulse, the discrepancy between the signal energies, all other things being equal, is clearly demonstrated. A connection has been established between the SNR when processing ultra-wideband signals at the output of the optimal receiver with similar devices for processing other types of signals, as well as with the SNR at the input of the receiving system. Systematization of the terminological features of the SNR concept will allow theoretical researchers to choose SNR definitions that are as close as possible to practical applications when analyzing the effectiveness of synthesized algorithms, and will allow practicing engineers to correctly interpret the results of theoretical calculations when developing or testing radio engineering systems.

Dynamic Characteristics Analysis of the DI-SO Cylindrical Spur Gear System Based on Meshing Conditions

The dual-input single-output (DI-SO) cylindrical spur gear system possesses advantages such as high load-carrying capacity, precise transmission, and low energy loss. It is increasingly becoming a core component of power transmission systems in maritime vessels, aerospace, marine engineering, and construction machinery. In practical operation, the stability of the DI-SO cylindrical spur gear system is influenced by complex excitations. These excitations lead to nonlinear vibration, meshing instability, and noise, which affect the performance and reliability of the entire equipment. Hence, the dynamic performance of the DI-SO cylindrical spur gear system is thoroughly investigated in this research. The impact of excitations and nonlinear factors on the dynamic characteristics was investigated comprehensively. A comparative analysis of the gear system was conducted by establishing a bending–torsional coupling vibration analysis model under synchronous and asynchronous meshing conditions. Nonlinear factors such as periodic time-varying meshing stiffness, meshing damping, friction coefficient, friction arms, load sharing ratio, comprehensive transmission error, and backlash were considered in the proposed model. Then, the effect laws of excitations and nonlinear factors such as meshing frequency, driving load fluctuation, backlash, and comprehensive transmission error were analyzed. The results indicate that the dynamic characteristics exhibited staged stable and unstable states under different meshing frequencies and meshing conditions. At the medium-frequency meshing stage (0.96 × 104~1.78 × 104 Hz), alternating phenomena of multi-periodic, quasi-periodic, and chaotic motion states were observed. Moreover, the root mean square value (RMS) of the dynamic transmission error (DTE) in the asynchronized gear system was generally higher than that in the synchronized gear system. It was found that selecting the appropriate meshing condition could effectively reduce the amplitude of the DTE. Additionally, the dynamic performance could be significantly improved by adjusting control parameters such as driving load fluctuation (0~179 N), backlash (0.8 × 10−4~0.9 × 10−4 m), and comprehensive transmission error (7.9 × 10−4~9.4 × 10−4 m). The research results provide a theoretical guidance for the design and optimization of the DI-SO cylindrical spur gear system.

Folding Imperfections: Mixed Methods Insight Into the Limits of Curriculum Change for the Trinidad and Tobago Primary School Curriculum Rewrite

We theorize on the limits of curriculum change in countries of the Caribbean and Global South using integrated evidence derived from a qualitatively driven, mixed methods evaluation (MME) of the Primary School Curriculum Rewrite (PCR) in Trinidad and Tobago. We use a folding metaphor and implementation science to explain how an imperfect system might produce a flawed curriculum product that misdirects sensemaking and generates resistance during curriculum change. The formative process evaluation consisted of two complete research projects, with the second qualitative project prioritized. Project 1 was a quantitative survey of 454 teachers in 58 schools. Project 2 was a multiple case study of subjectivities-in-action in 9 schools of varied implementation outcomes. Findings from Project 1 showed mostly acceptable implementation outcomes and small associations between antecedents and outcomes. However, findings from Project 2 suggested that 6 of 9 schools were classified as nonusers, defined as implementing institutions with most teachers still exploring or installing the new curriculum or reverting to the old curriculum. In the thematic, cross-case analysis, participants at the various sites identified curriculum imperfections, inadequate training, and work intensification as core barriers to change. To achieve curriculum change, Caribbean countries such as Trinidad and Tobago will require improved systems for curriculum engineering.

Auto-DSM: Using a Large Language Model to generate a Design Structure Matrix

The Design Structure Matrix (DSM) is an established method used in dependency modelling, especially in the design of complex engineering systems. The generation of DSM is traditionally carried out through manual means and can involve interviewing experts to elicit critical system elements and the relationships between them. Such manual approaches can be time-consuming and costly. This paper presents a workflow that uses a Large Language Model (LLM) to support the generation of DSM and improve productivity. A prototype of the workflow was developed in this work and applied on a diesel engine DSM published previously. It was found that the prototype could reproduce 357 out of 462 DSM entries published (i.e. 77.3%), suggesting that the work can aid DSM generation. A no-code version of the prototype is made available online to support future research.

Reversionary Control Modes for the Mitigation of Failures in a Partially Turboelectric Aircraft Propulsion System

Abstract In support of emission and fuel burn reduction goals, the aviation industry is actively pursuing the advancement of electrified aircraft propulsion (EAP) technology. This includes turboelectric and hybrid electric propulsion designs that combine gas turbine engine and electrical system hardware. Such architectures exhibit a high degree of coupling between subsystems. This drives the need for system-level control strategies to ensure the safe, coordinated, and efficient operation of all subsystems. The design and certification of any aircraft propulsion system requires that all potential subsystem failures are identified, and the hazards posed by these failures are appropriately mitigated. This requirement is particularly challenging for EAP systems due to their integrated nature. One approach to assist in EAP failure mitigation is the inclusion of automated reconfiguration capabilities within the propulsion control system. Such control modes, referred to as reversionary control modes, are designed to automatically detect failures and activate backup control modes upon failure detection. This paper covers the design and evaluation of reversionary control mode logic developed for a partially turboelectric propulsion concept. Test results from a real-time hardware-in-the-loop evaluation of the concept are also presented and discussed. The results show that the developed reversionary control logic can successfully detect and mitigate subsystem failures in a representative environment that includes actual electrical system hardware.

REAL-TIME PARAMETRIC DIAGNOSTICS OF MARINE DIESEL ENGINES

Using modern high-performance microcontrollers with wireless interfaces, built-in ADC and low overall consumption, it is possible to develop a portable real-time parametric diagnostic system for marine engines. The system is based on the use of modern Android/iOS gadgets that receive information from sensors via Bluetooth and then make the necessary calculations and display charts and data in real time. The system being developed uses a combination of a gas pressure sensor in the working cylinder and a vibroacoustic sensor, which expands the diagnostic capabilities of marine diesel engines under operating conditions. This solution makes it possible to diagnose the fuel injection system, the valves control mechanism, as well as some other engine systems. In order to develop a portable diagnostic system for marine diesel engines, it is first necessary to solve the problem of analytically determining TDC, since such a system does not involve the use of special sensors for this. Parameters of irregular engine operation are considered, which can be calculated in real time using time diagrams of pressure and vibration. Methods for expressly assessing the stability of the functioning of the main engine systems by monitoring and analyzing a number of successive operating cycles are considered. To assess the unevenness of engine operation, a dispersion estimate of deviations of the main parameters is used. For a comprehensive assessment of engine stability in real time, the CII (cycle’s irregularity index) criterion is proposed. The assessment of fuel injection irregularity in the engine cylinder can be carried out by analyzing the phase fronts of the vibration signal of the injector. Coefficients for assessing the irregularity of fuel injection and gas distribution valves timing are also proposed, using dispersion analysis of vibrograms fronts. The data processing methods proposed in the article will make it possible to analyze the stability of operating cycles, as well as to perform optimal tuning of engine systems and monitor the results during operation.

A Review of Differential Equations that is applicable to Differential Difference Equations

Mathematical modeling relies heavily on differential equations because they offer a robustframework for studying and understanding dynamical systems. However, the study of differential differenceequations (DDEs) has evolved as a subfield within differential equations due to the increasing prevalence ofsystems with discrete time steps and delayed effects. The purpose of this work is to present a synopsisof research on differential equations that may be used in the analysis of differential difference equations.The review starts with a thorough introduction to ODEs and PDEs (ordinary and partial differentialequations). Fundamental ideas, analytical approaches, and numerical strategies for solving thesecontinuous-time problems are discussed. ODEs and PDEs are highlighted for their importance insimulating a wide range of physical, biological, and engineering systems.

Energy-saving technology for harvesting root crops and potatoes

The purpose of the work is to empirically determine the temperature of the exhaust gases when changing the load on the power plant of a beet harvester with a separating system that provides better harvesting quality in conditions of high soil moisture. Have been developed: classification of methods for increasing the separating ability of slot-hole devices for cleaning root crops; laboratory installation for determining the quality indicators of a separation system with thermal energy for exhaust gas purification with a star-shaped cleaning device; a method for assessing the process of heat transfer from the exhaust gases of the power plant of the self-propelled harvester for harvesting sugar beets Holmer Terra Dos T3 to the separating system, which involves determining the temperature using thermocouples installed at various points in the gas exhaust system of the internal combustion engine. An experimental study of the temperature of the exhaust gases of the power plant of a harvesting machine was carried out using thermocouples at maximum rotation speed with a change in the thermal load index of the external environment from 5 to 30°C. The heat of the exhaust gases from the Mercedes-Benz power plant of the Holmer Terra Dos T3 self-propelled harvester, aimed at blowing the working surface of the separating device at the outlet of the first and fourth, as well as the second and third cylinders, has minor discrepancies exceeding the error limits (65 ± 5.8; 63.2 ± 1.5 and 74.9 ± 2.4; 75.2 ± 2.0°C, respectively), which leads to a uniform distribution of heat flow on the device for cleaning sugar beet roots.

Exploring the role of configurational accessibility of alleyways on facilitating wayfinding transportation within the organic street network systems

Despite the significant role of alleyways in urban spatial configuration and accessibility as critical structures of urban infrastructure, there remains a noticeable gap in understanding their specific role in urban transportation policies. The main aim of the present study is to investigate the role of configurational accessibility of alleyways in facilitating wayfinding within organic street network systems. A mixed method was applied using Space Syntax and empirical observations. Moreover, Pearson correlations and t-tests were used to discern the association between variables and compare independent groups using SPSS software. The findings from the syntactical analysis strongly indicate that alleyways significantly impact configurational accessibility within urban network systems. Furthermore, the complex and labyrinthine structure of organic alleyways was found to significantly hinder the intelligibility of urban areas, making navigation more challenging. The results revealed a significant correlation between vehicle mobility and connectivity values, with higher levels of mobility consistently linked to increased connectivity values. The outcomes also indicated that alleys connected to main streets play a crucial role in facilitating wayfinding within urban network systems. This study contributes to a more profound understanding of the role of alleyways in urban network systems for urban planners and transportation engineers, paving the way for more targeted sustainable urban planning strategies.

Photochromic webbing structures for monitoring UV-induced mechanical strength degradation

Abstract Webbing structures are critical load-bearing components in a wide array of applications from structural restraint layers in inflatable space habitats to safety harness belts used by construction workers. In the field, webbings are subjected to ultraviolet (UV) irradiation from sunlight, leading to material degradation and a loss of mechanical strength. To date, health monitoring of webbings has relied on empirically correlating UV-induced strength loss with variations in their inherent color, which often yields inconsistent and imprecise results. To fill this gap, we propose a novel class of photochromic webbing structures that afford noninvasive monitoring of UV-induced degradation of their mechanical strength. The webbings’ sensing capabilities are achieved by integrating a class of photochromic yarns, fabricated through a pressurized coating process. Under continuous UV irradiation, the proposed photochromic webbings exhibit a substantial color change, demonstrating a sensing lifetime equivalent to several months in field conditions. We establish a strong correlation between the webbings’ photochromic response and their strength loss, supporting the feasibility of the proposed webbings in monitoring their mechanical integrity. To elucidate the sensing mechanism, we propose a physics-based mathematical model that describes the underlying photochemical reactions. Through an asymptotic analysis, we demonstrate that the model accurately predicts the webbing’s long-term photochromic responses under extended UV irradiation. The proposed photochromic webbing structures and the predictive mathematical model could enhance the safety and integrity of webbing-based engineering systems.