Engineering Challenges Research Articles

Construction engineering to transform the composite frame of YY London

30 South Colonnade was a 13-storey composite framed office building, completed in the early 1990s as part of the first phase of London’s Canary Wharf redevelopment. Between 2020 and 2023 it was refurbished to become YY London, a highly sustainable modern workspace. A key aspect of the project has been retention and reuse of much of the existing structure, dramatically reducing the new development’s embodied carbon impact. This paper describes the way the composite steel-framed building’s original structural configuration was developed to accommodate the move to on-screen share trading in the 1980s. It then outlines the reasons that change why change was needed for the 2020s. A key feature of the construction engineering was demolition that disconnected several bays of the original bracing from the surrounding slab, requiring staged construction of temporary stability, and complicated by an unusual decision by the original designers.UNSDG 12 Responsible Consumption and Production is stimulating architect, engineers, and clients to propose more extensive reuse of structures and their embodied carbon. This paper describes the construction engineering challenges that these schemes generate for contracting teams, and some of the solutions that can be implemented to preserve and reuse the embodied carbon of composite buildings.

Engineering challenges in flash flood mitigation: insights from historical data and community perceptions in Tamanghasset, Algeria

Engineering challenges in flash flood mitigation: insights from historical data and community perceptions in Tamanghasset, Algeria

Explorando o potencial da gestão ágil na indústria da construção: uma revisão sistemática da literatura

To carry out more efficient and effective projects, those involved in project management in the construction industry seek alternatives to preserve projects' profit and value, manage change, improve communication with the client, and anticipate risks in the face of unforeseen events. In the face of uncertain and ever-changing scenarios, the Agile methodology has emerged to help the Architecture, Engineering, and Construction (AEC) sector face management challenges. This paper investigates the applicability of Agile methodology in construction project management. Insights from a state-of-the-art were mapped based on a systematic literature review and bibliometric analysis of 26 articles selected using criteria listed in the research protocol. A quantitative analysis of the distribution by year and country of publication and a qualitative analysis of the content were conducted, using codes managed by Atlas.ti software. The characterization of Agile management and the Scrum framework, the problems in construction projects, the application in the AEC industry and the conceptualization of the hybrid approach were analyzed. The authors discussed the main points surrounding the research and validated the benefits Agile adds to construction project management based on the literature.

Exploring innovative resilient and sustainable bio-materials for structural applications: Hemp-fibre concrete

Traditional construction is no longer practical in the modern competitive sustainability market, and growing urbanisation demands are paralleled by heightening concerns over the depletion of natural resources. Abundant renewability is offered in agriculture products for construction. A successful prototype is in the use of natural fibre, e.g., the commercially available hemp fibre (HF). Hemp is a widely accessible plant with flexible and sustainable cultivation processes possessing a positive carbon sequestration effect. HF possesses superior physio-mechanical properties, such as high tensile strength and excellent insulation capacity. The barrier to broader adoption lies in the nonuniformity inherent to natural materials and deficiencies imposed in using HF for composites, such as heightened permeability and slow setting, presenting engineering challenges that limit the suitability of HF to hydraulic mortars for non-structural applications. This paper aims to deliver a comprehensive state-of-the-art review of existing hemp fibre-reinforced concrete (HFRC) experiments towards identifying structural potential in various cementitious binders. In experimenting different arrangements of hemp in concrete, positive outcomes include increased flexural capacity, however, a loss in compressive strength and higher permeability are reported.

Collagen-hydroxyapatite based scaffolds for bone trauma and regeneration: recent trends and future perspectives.

Regenerative therapy, a key area of tissue engineering, holds promise for restoring damaged organs, especially in bone regeneration. Bone healing is natural to the body but becomes complex under stress and disease. Large bone deformities pose significant challenges in tissue engineering. Among various methods, scaffolds are attractive as they provide structural support and essential nutrients for cell adhesion and growth. Collagen and hydroxyapatite (HA) are widely used due to their biocompatibility and biodegradability. Collagen and nano-scale HA enhance cell adhesion and development. Thus, nano HA/collagen scaffolds offer potential solutions for bone regeneration. This review focuses on the use and production of nano-sized HA/collagen composites in bone regeneration.

Relative kinetic stability of defect patterns in two-dimensional nematic liquid crystals with rectangular confinement.

Guiding and dynamically modulating topological defects are critical challenges in defect engineering of liquid crystals. Here, we employ molecular dynamics simulations to investigate the transition dynamics and relative kinetic stability of defect patterns in two-dimensional nematic Gay-Berne liquid crystals confined within rectangular geometries. We observe the formation of various defect patterns including long-axis, diagonal, X-shaped, composite, and bend configurations under different confinement conditions. The competition between boundary effects and the uniformity of nematic orientation induces the continuous realignment of liquid crystal molecules, facilitating the spatially continuous transformation of defect patterns over time. This transition involves changes in both defect types and their locations, typically initiating from defect regions. Furthermore, we demonstrate that the relative stability of these defect patterns can be effectively controlled by adjusting confinement parameters and external field conditions. Our findings provide fundamental insights into the transition kinetics of defect patterns in confined nematic liquid crystals, thereby enhancing our ability to manipulate topological defects for advanced applications.

A weighted stabilized lagrange interpolation collocation method for boundary condition identification in 3D electromagnetic inverse scattering

The identification of boundary conditions in electromagnetic inverse scattering is of importance in various engineering applications, ranging from geophysical exploration to wireless communication. Conventional numerical methods solving this problem often suffer from the iterative process, leading to inefficiencies and non-convergence. This paper introduces a weighted scheme of the stabilized Lagrange interpolation collocation method (weighted SLICM) to resolve this problem. Weighted SLICM efficiently integrates governing equations, boundary conditions, and measurement conditions using a weighted least squares approach, offering a straightforward single-step solution and obviating the need for iterative processes in traditional methods like the finite element method. By incorporating regularization techniques, weighted SLICM decreases measurement errors which are unavoidable in engineering problems, thereby ensuring high efficiency and accuracy. In addition, characterized as a strong-form collocation method that relies solely on point information but not on grid connectivity, the weighted SLICM is readily extendible to complex three-dimensional applications in electromagnetic inverse scattering. Extensive simulations of benchmark problems show its ability to achieve accurate and stable results in boundary condition identification in electromagnetic inverse scattering problems including 1D, 2D, and 3D environments, highlighting the effectiveness of the weighted SLICM in navigating complex engineering challenges and substantially enriching research methodologies in this area.

Application of the Rosenblatt transformation in First-Order System Reliability approximations

The reliability assessment of structural systems presents a significant challenge in structural engineering. A commonly employed approximation is the First-Order System Reliability Method (FOSRM), which estimates system reliability using the FORM component reliabilities and sensitivity factors. An essential step in FORM involves transforming the random vector X into the standard vector U, often using the Rosenblatt transformation (RT). Several studies demonstrated that different conditioning orders in the RT yield different FORM component results. This study investigates how these differences on component level propagate into the FOSRM system level. We conducted several typical engineering case studies with various failure probabilities, system sizes, and dependency structures (Gaussian and Frank Copula). For the Frank Copula, different Rosenblatt conditioning orders systematically yielded different FOSRM results, with most cases showing differences between 10% and 30% in estimated failure probability. For some systems, these differences increased with system size, suggesting that greater variations might be observed for larger systems. Notably, systems with Gaussian Copula functions also proved vulnerable to the Rosenblatt conditioning order when different components were assessed with different conditioning orders. The observed differences were larger than previously reported and should be carefully considered in uniform safety assessments.

Enhancing pavement crack segmentation via semantic diffusion synthesis model for strategic road assessment

Computer-aided deep learning has significantly advanced road crack segmentation. However, supervised models face challenges due to limited annotated images. There is also a lack of emphasis on deriving pavement condition indices from predicted masks. This article introduces a novel semantic diffusion synthesis model that creates synthetic crack images from segmentation masks. The model is optimized in terms of architectural complexity, noise schedules, and condition scaling. The optimal architecture outperforms state-of-the-art semantic synthesis models across multiple benchmark datasets, demonstrating superior image quality assessment metrics. The synthetic frames augment these datasets, resulting in segmentation models with significantly improved efficiency. This approach enhances results without extensive data collection or annotation, addressing a key challenge in engineering. Finally, a refined pavement condition index has been developed for automated end-to-end defect detection systems, promoting more effective maintenance planning.

Power system stability enhancement through optimal PSS design

Low-frequency oscillations (LFO) are generated in interconnected electric networks because of the weak tie lines between the parts of the networks. Such oscillations have been a significant challenge for engineers that may lead to system instability if appropriate measures are not taken. This article proposes two new metaheuristic algorithms, the jellyfish search algorithm (JSA) and the tunicate swarm algorithm (TSA), to design the power system stabilizers (PSS) for single machine infinite bus (SMIB) and multimachine power system (MPS) networks. The proposed method uses the JSA and TSA to dampen out the LFOs by modifying the vital parameters of lead-lag type conventional PSS (CPSS). A damping ratio-based objective function improves both models' system damping. These methods are tested on an SMIB system and two distinct MPS networks exposed to the three-phase fault under various loading conditions. The effectiveness of the suggested approach has been studied by comparing the system eigenvalues and minimum damping ratio (MDR) produced from JSA and TSA-tuned PSS and the CPSS. In addition, time domain simulation results are compared, demonstrating that the new approach outperforms the standard techniques, such as particle swarm optimization (PSO) and backtracking search algorithm (BSA). In the SMIB system, MDR produced by JSA and TSA-based PSS is 2.55 times higher than that of CPSS. Similarly, in comparison to PSO and BSA-based PSS, JSA, and TSA-tuned PSS offer >1.4 times greater MDR in the Two Area Four Machine network and up to 8.4 times larger MDR for the IEEE-39 Bus network. Furthermore, the efficacy of the suggested JSA and TSA approaches' prediction capacity is validated by satisfying the values of statistical performance metrics.

Generating Stochastic Structural Planes Using Statistical Models and Generative Deep Learning Models: A Comparative Investigation

Structural planes are one of the key factors controlling the stability of rock masses. A comprehensive understanding of the spatial distribution characteristics of structural planes is essential for accurately identifying key blocks, analyzing rock mass stability, and addressing various rock engineering challenges. This study compares the effectiveness of four stochastic structural plane generation methods—the Monte Carlo method, the Copula-based method, generative adversarial networks (GAN), and denoised diffusion models (DDPM)—in generating stochastic structural planes and capturing potential correlations between structural plane parameters. The Monte Carlo method employs the mean and variance of three parameters of the measured factual structural planes to generate data that follow the same distributions. The other three methods take the entire set of measured factual structural planes as the overall input to generate structural planes that exhibit the same probability distributions. Five sets of structural planes on four rock slopes in Norway are examined as an example. The validation and analysis were performed using histogram comparison, data feature comparison, scatter plot comparison, and linear regression analysis. The results show that the Monte Carlo method fails to capture the potential correlation between the dip direction and dip angle despite the best fit to the measured factual structural planes. The Copula-based method performs better with smaller datasets, and GAN and DDPM are better at capturing the correlation of measured factual structural planes in the case of large datasets. Therefore, in the case of a limited number of measured structural planes, it is advisable to employ the Copula-based method. In scenarios where the dataset is extensive, the deep generative model is recommended due to its ability to capture complex data structures. The results of this study can be utilized as a valuable point of reference for the accurate generation of stochastic structural planes within rock masses.

Effect and mechanism of accelerated carbonization on the adhesion property of asphalt mixture containing recycled concrete aggregate

Weak interfacial adhesion between asphalt and recycled concrete aggregate (RCA) poses a significant engineering challenge in asphalt pavements. Accelerated carbonization treatment effectively enhances the performance of RCA by filling microcracks and pores in the mortar on its surface. This study investigated the optimal carbonization time, balancing economic feasibility, using boiling water experiments, pull-off tests, X-ray diffraction, and thermogravimetric analysis. Changes in the micro-morphology of the RCA surface at various carbonization times were observed using scanning electron microscopy. Molecular dynamics simulation was then employed to analyze the mechanism by which accelerated carbonization affects the adhesion properties of asphalt mixtures containing RCA. The results indicate that interfacial adhesion between RCA and asphalt gradually improves with increasing carbonization time. After 48 hours of carbonization, the asphalt adhesion rate increased from 52.7 % to 92.2 %, and the tensile strength rose from 1.13 MPa to 2.85 MPa. As the carbonization reaction progresses, spherical vaterite, acicular aragonite and massive calcite in lump form gradually appear on the RCA surface. Eventually, a calcium carbonate film forms and adheres to the RCA surface, enhancing adhesion properties at the RCA-asphalt interface. At the molecular level, carbonization significantly increased the concentrations of asphaltenes, aromatics, and saturates near the interface. The interaction energies between RCA and asphaltenes, aromatics, saturates, and resins increased by 97.5 %, 51.4 %, 35.7 %, and 6.0 %, respectively. Accelerated carbonization offers a viable solution for incorporating RCA in hot-mix asphalt, contributing to the sustainability of pavement infrastructure.

Environmental Ethics Challenges for Engineers and How to Address Them

Engineers are the core of modern engineering activities, the designers, managers, implementers and supervisors of engineering activities. The special social role of engineers determines that they must take more moral responsibility, not only to the public and others, but also to the environment and the future of mankind. Nowadays, environmental and resource problems have become a major issue that restricts economic development and affects people's life and health.Engineers are facing more challenges from environmental ethics. For example, how to harmonize the relationship between economic and ecological interests, and between the interests of the present generation and those of the future generations, and the weak awareness of environmental ethical responsibility and insufficient ability to protect the environment among some engineers. To cope with these challenges, it is necessary for engineers to make efforts on their own and for society as a whole to work together to form internal and external safeguard mechanisms for engineers to fulfill their environmental ethical responsibilities.

Battersea power station – regeneration of an icon

Since decommissioning in 1983 Battersea Power Station was untouched: the iconic structure proved challenging to repurpose and, exposed to the elements with degrading condition, it quickly evolved into London's most notorious ruin. The restoration of the structure started in 2012, with the completed building opening in 2022. The engineering and construction challenges of the project were vast. Often referred to “The Everest of Real Estate”, reflecting its scale and complexity, the engineering and construction challenges revolved around preserving the existing fabric and installing a new structure within the existing shell to facilitate the new mix-used development. The approach to the redevelopment has been to adopt a ‘light touch’ and sympathetic approach, with a drive to reuse as much structure as possible. Consequently, reuse of the existing structures, including internal structures and refurbishment of the existing brickwork have led to a reuse of more than 44,000 tons of CO2e of legacy carbon, equivalent to around 20% of the total embodied carbon in the completed structure. The completed project has led the way for the social, economic, and environmental transformation to the Vauxhall and Nine Elms area, creating a new town centre for Wandsworth with a community of homes, shops, cafes, offices and over 19 acres of public space.

Rock slope stability analysis of a limestone quarry in a case study of a National Cement Factory in Eastern Ethiopia

Rock slope failures pose significant challenges in geotechnical engineering due to the intricate nature of rock masses, discontinuities, and various destabilizing factors during and after excavation. In mining industries, such as national cement factories, multi-benched excavation systems are commonly used for quarrying. However, cut slopes are often designed with steep angles to maximize economic benefits, inadvertently neglecting critical slope stability issues. This oversight can lead to slope instability, endangering human lives and property. This study focuses on analyzing the stability of existing quarry cut slopes, estimating their final depth, and conducting a parametric study of geometric profiles including bench height, width, face angle, and rump width. Kinematic analysis helps identify potential failure modes. The results reveal that the existing quarry cut slope is prone to toppling, wedge failure, and planar failure with probabilities of 42.68%, 19.53%, and 14.23%, respectively. Numerical modeling using the finite element method (Phase2 8.0 software) was performed under both static and dynamic loading conditions. The shear reduction factor (SRF) of the existing quarry cut slope was 1.01 under static loading and 0.86 under dynamic loading. Similarly, for the estimated depth, the SRF was 0.82 under static loading and 0.7 under dynamic loading. These values indicate that the slope stability falls significantly below the minimum acceptable SRF, rendering it unstable. The parametric study highlights the face angle of the bench as the most influential parameter in slope stability. By adjusting the bench face angle from 90° to 75°, 70°, and 65°, the SRF increased by 31.6%, 35.4%, and 37.9%, respectively. Among these, a 70° bench face angle is recommended for optimal stability with a SRF of 1.27 under static loading and 1.18 under dynamic loading.

In-Situ and in-Operando Li-Ion Batteries for Materials Science Education

Electrochemical energy storage systems, particularly Li-ion rechargeable batteries (LiRB), have a key role to play in fortifying US energy generation, decarbonizing the electricity sector, and limiting anthropogenic climate change. LiRBs suffer from limited lifetimes, insufficient energy densities, and fire risks, which are all materials science and engineering challenges stemming from various irreversible degradation processes occurring at nano and micro-scales. These batteries function via the reversible diffusion of Li ions from a Li-rich cathode to a Li-poor anode, each of which undergo various levels of volumetric phase changes, plastic deformation, and microcracking with each charging cycle, thereby compromising subsequent battery performance. Therefore, it is imperative to understand the nano-mechanical processes associated with LiRB degradation and predict transformative material designs that can lead to manufacturing cheaper, denser, and safer LiRBs. Such understanding and design would be instrumental to achieving the US 2050 Net Zero Goal. Additionally, the US lags 10x behind China in terms of Li battery manufacturing capability, and thus a LiRB-aware Research and Development workforce is paramount for continued US energy security. In this context, we propose a new design for in-situ and in-operando Li-ion battery research and education. This battery design will be used in a classroom/lab setting to discuss fundamental materials science concepts such as diffusion, grain-boundaries, and fracture. This activity will be used to broaden "missing millions" student participation in a crucial area of energy research at a minority serving institution.

Client-Server Code Mobility at Runtime

Application logic is inherently distributed between client and server due to the fundamental Client/Server architecture of the Web. The individual distribution is specified at design time and remains unchanged stable, preventing individual load distribution between clients and server at runtime. Dynamic code mobility at runtime, in contrast, allows to balance the needs of users, through increased responsiveness, and software providers, through better resource usage and cost reductions. Enabled by WebAssembly, the Web ecosystem recently provides the technological foundation for relocating code units during runtime. However, leveraging these capabilities to enhance web applications with dynamic code migration presents challenges for web engineers. In response, we propose an innovative distributed Client/Server software architecture for web applications. This architecture facilitates the dynamic migration of code at runtime, and addresses the technical challenges like dependency management, control and data flow distribution, communication, and interfaces. This novel software architecture serves as a reference for web engineers aiming to enrich their web applications with dynamic code mobility. Additionally, it contributes to the ongoing reevaluation of the Web ecosystem in light of the widespread adoption and standardization of WebAssembly across major browsers. Through experimentation in four scenarios, we demonstrate the feasibility of implementing this architecture, its negligible impact on performance and the optimization potential for individual code distributions across client and server.

Evaluating soil freezing characteristic curve models for predicting unfrozen water content in freezing soils

Frozen soil is widely distributed around the world, and the phase change and migration of ice and water contribute to various engineering and agricultural challenges. The Soil Freezing Characteristic Curve (SFCC), which elucidates the relationship between water and temperature in permafrost, serves as a crucial tool for studying permafrost and forms the foundational equation for coupled numerical simulations involving permafrost water-heat-force. Different choices of SFCC result in variations in the predicted values of unfrozen water, thereby affecting the accuracy of other issues or numerical simulations. Moreover, there is a lack of studies on the performance of SFCC models under diverse conditions. Therefore, we review and classify some existing SFCC models, selects 14 SFCC models according to functional form, derivation process, physical significance etc., and evaluates these models through published data and statistical indicator RMSE, Radj2 and BIC. The effects of functional form, soil type, cooling stage and initial water content on each model were analyzed using cluster analysis and other means. It is concluded that the SFCC model is affected by the function form, and the power and exponential functions need to be modified by more parameters. The nested soil water characteristic curve model also needs to be modified for the low water content section. Meanwhile, each model also shows sensitivity to the characteristics of datasets, and the performance under different conditions is not the same. Some models may not fit data features under certain conditions. Therefore, it is necessary to reasonably select the SFCC model in different use backgrounds and conditions.

An integrated cyberinfrastructure system for water quality resources in the Upper Mississippi River Basin

ABSTRACT The Upper Mississippi Information System (UMIS) is a cyberinfrastructure framework designed to support large-scale real-time water-quality data integration, analysis, and visualization for the Upper Mississippi River Basin (UMRB). UMIS is intended to directly address three of the Grand Challenges for Engineering including (1) understanding access to clean drinking water, (2) management of the nitrogen cycle, and (3) engineering the tools of scientific discovery. The UMIS is designed to provide significant immediate and long-term impacts including a central platform for data access, integration, discovery, and adoption of cyberinfrastructure tools and services. The UMIS demonstrates that public data aggregators and central repositories can provide important services to anyone interested in water-quality research or education. In addition, working across multiple scales (e.g., state, region, county, or watershed) allows researchers to understand broad and narrow effects of water-quality strategies. Exploration of data across these scales encourages the development of problem-based research questions that can eventually provide feedback to public policies.

Engineering a Sinorhizobium meliloti Chassis with Monopartite, Single Replicon Genome Configuration.

Multipartite bacterial genomes pose challenges for genome engineering and the establishment of additional replicons. We simplified the tripartite genome structure (3.65 Mbp chromosome, 1.35 Mbp megaplasmid pSymA, 1.68 Mbp chromid pSymB) of the nitrogen-fixing plant symbiont Sinorhizobium meliloti. Strains with bi- and monopartite genome configurations were generated by targeted replicon fusions. Our design preserved key genomic features such as replichore ratios, GC skew, KOPS, and coding sequence distribution. Under standard culture conditions, the growth rates of these strains and the wild type were nearly comparable, and the ability for symbiotic nitrogen fixation was maintained. Spatiotemporal replicon organization and segregation were maintained in the triple replicon fusion strain. Deletion of the replication initiator-encoding genes, including the oriVs of pSymA and pSymB from this strain, resulted in a monopartite genome with oriC as the sole origin of replication, a strongly unbalanced replichore ratio, slow growth, aberrant cellular localization of oriC, and deficiency in symbiosis. Suppressor mutation R436H in the cell cycle histidine kinase CckA and a 3.2 Mbp inversion, both individually, largely restored growth, but only the genomic rearrangement recovered the symbiotic capacity. These strains will facilitate the integration of secondary replicons in S. meliloti and thus be useful for genome engineering applications, such as generating hybrid genomes.