Introduction
The world is currently undergoing turbulent development. Preparations for a world war are
underway. Geostrategists have been analyzing the changing international situation for several
years now. Further dates and potential locations for a major conflict are being set. The topic is
common knowledge in many parts of the world.
Cities have been selected for nuclear attack, and potential spheres of influence have
been defined. Since 2022, industrial companies have been preparing for what may soon
happen. As a society, we are receiving information and even instructions, such as a "safety
guide," on how to behave in this hour of testing.
This paper presents several general observations based on, among other things, known
history and the many discussions that have been taking place in Lower Silesia over the years.
It also outlines development concepts that could be implemented after the end of any potential
conflict.
Highway engineering. Roads and pavements, Bridge engineering
Igor Chernenko, Oksana Bilonoh, Serhii Yanishevskyi
et al.
Introduction. The article proposes methodological approaches to the implementation of the provisions of the concept of sustainable development in the management of transport service processes of economic entities in terms of reducing the negative impact on the environment from vehicles as mobile sources of pollution.
Issues. The latest statistical data on the environmental situation in our country indicate the relevance of the topic of this study. The negative impact on the environment caused by stationary and mobile sources of pollution is significant in terms of total emissions, although it tends to decrease. Stationary sources of pollution, which include enterprises of various industries, account for approximately 30 % of the total emissions. The largest contribution to these emissions is made by enterprises in the electricity generation sector (over 36 %) and the metallurgical sector (over 24 %). The contribution of road transport to total emissions, depending on the region, is over 45 %. The main emissions caused by motor vehicles are carbon dioxide, carbon monoxide, nitrogen oxides, and volatile organic compounds.
The purpose of the work is to formulate proposals and develop a mechanism for the practical implementation of sustainable development approaches in the management of transport service processes of economic entities.
Presently, many asphalts and modified asphalts fail to satisfy long-term serviceability and durability criteria. Researchers are utilizing several asphalt modifiers to enhance the overall performance of flexible pavements. This study consolidated findings from multiple research efforts on using nanomaterials for modifying SBS modified asphalt (SBS MA) and conducted a comprehensive literature review. Initially, it discussed the importance of SBS MA within asphalt modification systems and identified the key nanomaterials utilized in SBS modified asphalt. After this, it reviewed their preparation methods, dispersion and characterization techniques, and their impact on the key performance parameters of SBS MA binder and its mixture such as viscosity, rutting resistance, fatigue resistance, ageing and moisture damage etc. Additionally, it highlighted the advantages of nanomaterials over other modifiers. This study also addressed the challenges and limitations of incorporating nanomaterials in SBS MA. The findings indicated that when properly integrated, nanomaterials could significantly improve the performance of SBS MA, making them a promising addition to future road construction and maintenance projects. However, using nanomaterials for SBS MA modifications and mixtures has been challenged by limited practical applications, insufficient life cycle cost analyses, a lack of standardized guidelines, cost-effective nanomaterials and insufficient mixing procedures. Those areas require additional research to realise the potential application of nanomaterials in SBS modified asphalt modifications full.
Highway engineering. Roads and pavements, Engineering (General). Civil engineering (General)
This study investigates the stability of skeleton-reinforced concrete arch bridges during the concrete encasement process, employing a homogeneous generalized yield functions for extreme buckling load determination in nonlinear finite element analysis. Through an analysis of the stability of a stiff skeleton arch bridge with a 600 m span during the concrete wrapping stage, this study delves into and elucidates the mechanism by which the transverse brace enhances the out-of-plane stability capacity of the skeleton arch ribs. Additionally, a method for improving stability by controlling the lateral rotation angle of arch ribs is proposed. The results indicate that the lateral deflection angle of arch ribs serves as a crucial metric for assessing the out-of-plane stability of arch bridges. Transverse braces effectively coordinate and constrain the lateral deflections of two isolated arch ribs through their bending stiffness along the tangential direction of the arch axis. Notably, transverse braces within the range of L/8 to 3L/8 make the most substantial contribution to the lateral stiffness of arch ribs. Consequently, wrapping surrounding concrete on transverse braces within the L/8 to 3L/8 range proves advantageous for enhancing the stability of a stiff skeleton arch bridge under construction. Specifically, it is recommended to pour surrounding concrete on transverse braces at L/4 before the closure of the bottom plate’s concrete ring. After the ring of bottom plate’s concrete is closed, a symmetrical pouring of surrounding concrete on transverse braces from L/4 to the arch spring and vault is proposed.
Highway engineering. Roads and pavements, Bridge engineering
Large Language Models (LLMs) are revolutionizing software engineering (SE), with special emphasis on code generation and analysis. However, their applications to broader SE practices including conceptualization, design, and other non-code tasks, remain partially underexplored. This research aims to augment the generality and performance of LLMs for SE by (1) advancing the understanding of how LLMs with different characteristics perform on various non-code tasks, (2) evaluating them as sources of foundational knowledge in SE, and (3) effectively detecting hallucinations on SE statements. The expected contributions include a variety of LLMs trained and evaluated on domain-specific datasets, new benchmarks on foundational knowledge in SE, and methods for detecting hallucinations. Initial results in terms of performance improvements on various non-code tasks are promising.
Proto-personas are commonly used during early-stage Product Discovery, such as Lean Inception, to guide product definition and stakeholder alignment. However, the manual creation of proto-personas is often time-consuming, cognitively demanding, and prone to bias. In this paper, we propose and empirically investigate a prompt engineering-based approach to generate proto-personas with the support of Generative AI (GenAI). Our goal is to evaluate the approach in terms of efficiency, effectiveness, user acceptance, and the empathy elicited by the generated personas. We conducted a case study with 19 participants embedded in a real Lean Inception, employing a qualitative and quantitative methods design. The results reveal the approach's efficiency by reducing time and effort and improving the quality and reusability of personas in later discovery phases, such as Minimum Viable Product (MVP) scoping and feature refinement. While acceptance was generally high, especially regarding perceived usefulness and ease of use, participants noted limitations related to generalization and domain specificity. Furthermore, although cognitive empathy was strongly supported, affective and behavioral empathy varied significantly across participants. These results contribute novel empirical evidence on how GenAI can be effectively integrated into software Product Discovery practices, while also identifying key challenges to be addressed in future iterations of such hybrid design processes.
Alexandra Mazak-Huemer, Christian Huemer, Michael Vierhauser
et al.
With the increasing significance of Research, Technology, and Innovation (RTI) policies in recent years, the demand for detailed information about the performance of these sectors has surged. Many of the current tools are limited in their application purpose. To address these issues, we introduce a requirements engineering process to identify stakeholders and elicitate requirements to derive a system architecture, for a web-based interactive and open-access RTI system monitoring tool. Based on several core modules, we introduce a multi-tier software architecture of how such a tool is generally implemented from the perspective of software engineers. A cornerstone of this architecture is the user-facing dashboard module. We describe in detail the requirements for this module and additionally illustrate these requirements with the real example of the Austrian RTI Monitor.
Jannatul Bushra, Md Habibor Rahman, Mohammed Shafae
et al.
Reverse engineering can be used to derive a 3D model of an existing physical part when such a model is not readily available. For parts that will be fabricated with subtractive and formative manufacturing processes, existing reverse engineering techniques can be readily applied, but parts produced with additive manufacturing can present new challenges due to the high level of process-induced distortions and unique part attributes. This paper introduces an integrated 3D scanning and process simulation data-driven framework to minimize distortions of reverse-engineered additively manufactured components. This framework employs iterative finite element simulations to predict geometric distortions to minimize errors between the predicted and measured geometrical deviations of the key dimensional characteristics of the part. The effectiveness of this approach is then demonstrated by reverse engineering two Inconel-718 components manufactured using laser powder bed fusion additive manufacturing. This paper presents a remanufacturing process that combines reverse engineering and additive manufacturing, leveraging geometric feature-based part compensation through process simulation. Our approach can generate both compensated STL and parametric CAD models, eliminating laborious experimentation during reverse engineering. We evaluate the merits of STL-based and CAD-based approaches by quantifying the errors induced at the different steps of the proposed approach and analyzing the influence of varying part geometries. Using the proposed CAD-based method, the average absolute percent error between simulation-predicted distorted dimensions and actual measured dimensions of the manufactured parts was 0.087%, with better accuracy than the STL-based method.
In the past, the rapid development of transportation infrastructure brought about a boom in transportation. Nowadays, a large number of transportation infrastructure has begun to enter the maintenance stage, especially a large number of highways have begun to need maintenance and repair in order to maintain normal operation and use. How to develop an efficient and reasonable maintenance plan needs to be judged according to the real road conditions on site. It is an important task to identify the existing damage on the road surface. At present, the detection of pavement cracks is inefficient and expensive. To solve this problem, an improved YOLOv4 pavement crack target detection model was proposed. Firstly, MobileNetv2 is used as the backbone network and other common convolution is replaced by deeply separable convolution. Secondly, coordinate attention mechanism and spatial attention mechanism are implanted into Backbone and Neck respectively. The experimental results show that the improved model can further improve the accuracy of pavement crack detection and greatly improve the detection speed, the FPS can reach 61.48 frames/s, and the mAP can reach 67.26%, which is greatly improved compared with the original model.
In civil engineering, the study of embankment settlement on soft ground is a vital geotechnical task in order to maintain serviceability of the road embankment, pavement, and facilities. This paper presents a study on settlements of road embankment on soft ground using vertical drains, including prefabricated-vertical drain (PVD), sand drain (SD), and sand compaction pile (SCP) on a number of packages of Hanoi – Haiphong Expressway Construction Project. The effectiveness of settlement prediction of vertical drain solutions is evaluated considering the ratios between the observed consolidation settlements and settlements predicted in the Detailed Design, in relation to the thickness of soft soil and the depth of treatment. Regression analysis is used to establish the correlation between the observed settlement and the height of embankment. The results show that (i) the design generally overestimated settlements; (ii) the ratios between observed and predicted settlements tend to positively correlate with the thickness of soft soil and the depth of treatment, and (iii) there are positive correlations between the height of embankment and the observed settlement. These correlations can be a valuable source of reference for anticipating settlements in basic design of highway projects with soft ground treated by vertical drains, in the regions that have geological stratum similar to Thabinh and Haihung formations of Bacbo Plain
The creation of a Software Requirements Specification (SRS) document is important for any software development project. Given the recent prowess of Large Language Models (LLMs) in answering natural language queries and generating sophisticated textual outputs, our study explores their capability to produce accurate, coherent, and structured drafts of these documents to accelerate the software development lifecycle. We assess the performance of GPT-4 and CodeLlama in drafting an SRS for a university club management system and compare it against human benchmarks using eight distinct criteria. Our results suggest that LLMs can match the output quality of an entry-level software engineer to generate an SRS, delivering complete and consistent drafts. We also evaluate the capabilities of LLMs to identify and rectify problems in a given requirements document. Our experiments indicate that GPT-4 is capable of identifying issues and giving constructive feedback for rectifying them, while CodeLlama's results for validation were not as encouraging. We repeated the generation exercise for four distinct use cases to study the time saved by employing LLMs for SRS generation. The experiment demonstrates that LLMs may facilitate a significant reduction in development time for entry-level software engineers. Hence, we conclude that the LLMs can be gainfully used by software engineers to increase productivity by saving time and effort in generating, validating and rectifying software requirements.
Large Language Models (LLMs) have shown prominent performance in various downstream tasks and prompt engineering plays a pivotal role in optimizing LLMs' performance. This paper, not only as an overview of current prompt engineering methods, but also aims to highlight the limitation of designing prompts based on an anthropomorphic assumption that expects LLMs to think like humans. From our review of 50 representative studies, we demonstrate that a goal-oriented prompt formulation, which guides LLMs to follow established human logical thinking, significantly improves the performance of LLMs. Furthermore, We introduce a novel taxonomy that categorizes goal-oriented prompting methods into five interconnected stages and we demonstrate the broad applicability of our framework. With four future directions proposed, we hope to further emphasize the power and potential of goal-oriented prompt engineering in all fields.
In the quest for more sustainable pavement solutions, this study demonstrates the successful strengthening of a unique noise-reducing two-layer road surface. While existing noise-reducing pavements reveal high acoustic efficiency, they lack mechanical strength, and earlier research efforts addressed the optimization of the individual components of this system, and a comprehensive perspective on its integrated performance remained elusive. Therefore, this research bridges this knowledge gap through an in-depth laboratory evaluation, in which the requirements for the realization of a full-scale demonstrator were defined, followed by a comprehensive performance assessment in terms of acoustic and mechanical strength. The post-construction assessment reveals the system’s multifaceted strengths, considering noise reduction, resilience under heavy traffic, pavement deflections, and skid resistance, assessed by CPX measurements, accelerated pavement tests using the MLS 30, skid resistance tests employing the pendulum test, as well as the slow-moving longitudinal friction test (MicroGriptester) and falling weight deflectometer (FWD) measurements. Although the optimized system implies lower noise-reduction potential, it exhibits great strength compared to previous noise-reducing pavements. In general, the system offers viable noise mitigation solutions for urban highways, particularly in settings where traditional noise abatement measures are constrained by space. The insights from this study serve as a valuable reference for the development and evaluation of innovative road engineering materials and technologies.
Introduction. Increasing the durability of hard pavements allows you to reduce road maintenance costs by extending the intervals between repairs. Dispersed reinforcement is a well-known method of increasing the frost resistance and abrasion resistance of concrete, which has a positive effect on the durability of pavements in typical for Ukraine climatic conditions. Basalt fiber is resistant to corrosion and relatively inexpensive, which makes it promising for use in the road industry. Also, plasticizing and air-entraining admixtures must be used for concrete of hard pavement.
Problem Statement. In modern economic conditions and taking into account the technological features of the preparation of mixtures, it is relevant to compare the effectiveness of the use of known methods of improving the properties of concrete for hard pavements: dispersed reinforcement and the use of air-entraining admixtures. Studying the expediency of the simultaneous use of these two methods of modifying the concrete mixture is also an important task from a scientific and practical point of view.
Purpose. Determination of the influence of basalt fiber and air-entraining admixture on the strength, frost resistance and abrasion resistance of concrete of hard pavements.
La rehabilitación de pavimentos deteriorados requiere de diversos recursos tanto naturales como económicos. Ante tal problemática, esta investigación tuvo como objetivo elaborar un diseño de mezcla para la estabilización de un suelo reciclado con emulsión asfáltica tipo CSS-1h, utilizando el método de diseño Marshall modificado. El estudio analizó la influencia del porcentaje de emulsión asfáltica (3,0 % a 6,0 %) respecto a las propiedades físicas y mecánicas del suelo estabilizado según los parámetros que exige el manual peruano de carreteras EG-2013.
Los resultados muestran que, con una dosificación de 4,8 % de emulsión asfáltica y 2,88 % de residuo asfáltico se logra el mejor comportamiento en comparación a los demás porcentajes planteados, obteniendo una máxima estabilidad de 980 kg superando el mínimo valor de 227 kg establecido por la norma. Se concluyó que con dicha dosificación se obtiene una mezcla asfáltica estable con la que se puede estabilizar el pavimento deteriorado para soportar un tránsito vehicular mediano.
Automatic pavement crack detection is an important task to ensure the functional performances of pavements during their service life. Inspired by deep learning (DL), the encoder-decoder framework is a powerful tool for crack detection. However, these models are usually open-loop (OL) systems that tend to treat thin cracks as the background. Meanwhile, these models can not automatically correct errors in the prediction, nor can it adapt to the changes of the environment to automatically extract and detect thin cracks. To tackle this problem, we embed closed-loop feedback (CLF) into the neural network so that the model could learn to correct errors on its own, based on generative adversarial networks (GAN). The resulting model is called CrackCLF and includes the front and back ends, i.e. segmentation and adversarial network. The front end with U-shape framework is employed to generate crack maps, and the back end with a multi-scale loss function is used to correct higher-order inconsistencies between labels and crack maps (generated by the front end) to address open-loop system issues. Empirical results show that the proposed CrackCLF outperforms others methods on three public datasets. Moreover, the proposed CLF can be defined as a plug and play module, which can be embedded into different neural network models to improve their performances.
For the past few decades, researchers all over the world have agreed that the service life of civil infrastructure is significantly affected by climate change. Pavement is one of these significant infrastructures that can be easily affected by climate change. However, it is well known that predicting climate change is highly complex and dynamic. Hence, a review has been done on available climate change models and the uncertainties involved in climate change prediction. This review addresses various important questions, such as (i) what climate change is, (ii) how to use climate change models, (iii) uncertainties involved in using climate change models, (iv) how climate change impacts pavement infrastructure, (v) the adaptation and mitigation strategies available, and (vi) how economic costs and emissions change due to climate change. This review is useful to understand climate change and its implications on pavement infrastructure.
Motorcyclists involved in 74% road traffic accidents (RTA) in Indonesia and the majority were students. WHO reported that 74% of RTA death victims were motorcyclists. This research aimed at analysing student trip and mode characteristics by using Revealed Preference survey. Majority of students were found using motorcycles due to travel time and cost. Average travel and waiting times are 18.5 and 0.1 minutes. Average travel cost varies between Rp.3750-Rp.4950. The ratio between students categorized as captive and choice users are 75%;25%. Majority of students depart before 07.00 AM and end their trips before 3 PM. In order to encourgae students to shift to public transport, the Trans Padang service is recommended to be integrated with parking facilities which is the direction of the future research.
Highway engineering. Roads and pavements, Engineering (General). Civil engineering (General)
Background: Classifications in meta-research enable researchers to cope with an increasing body of scientific knowledge. They provide a framework for, e.g., distinguishing methods, reports, reproducibility, and evaluation in a knowledge field as well as a common terminology. Both eases sharing, understanding and evolution of knowledge. In software engineering (SE), there are several classifications that describe the nature of SE research. Regarding the consolidation of the large body of classified knowledge in SE research, a generally applicable classification scheme is crucial. Moreover, the commonalities and differences among different classification schemes have rarely been studied. Due to the fact that classifications are documented textual, it is hard to catalog, reuse, and compare them. To the best of our knowledge, there is no research work so far that addresses documentation and systematic investigation of classifications in SE meta-research. Objective: We aim to construct a unified, generally applicable classification scheme for SE meta-research by collecting and documenting existing classification schemes and unifying their classes and categories. Method: Our execution plan is divided into three phases: construction, validation, and evaluation phase. For the construction phase, we perform a literature review to identify, collect, and analyze a set of established SE research classifications. In the validation phase, we analyze individual categories and classes of included papers. We use quantitative metrics from literature to conduct and assess the unification process to build a generally applicable classification scheme for SE research. Lastly, we investigate the applicability of the unified scheme. Therefore, we perform a workshop session followed by user studies w.r.t. investigations about reliability, correctness, and ease of use.
In order to reduce the differential settlement of the extended urban highway splicing segment, we monitored the junction of the new and old subgrade in the practical engineering, analyzed the value of pavement deformation. It found that the smaller the modulus ratio of the new and old subgrade, the greater the non-uniform settlement value. At the same time, the uneven settlement and lateral displacement of the road can be effectively reduced by using the pile-reinforced cushion structure. So the results show that the pile-reinforced cushion structure can effectively reduce the uneven settlement and lateral displacement of the old and new roads, strengthen the links between old and new roads; To enhance the stability of subgrade, it can be used for widening the old road in soft soil foundation.