This paper presents the results of two surveys conducted by the American Society of Civil Engineers’ Task Committee on Computing Education of the Technical Council on Computing and Information Technology to assess the current computing component of the curriculum in civil engineering. Previous surveys completed in 1989 and 1995 have addressed the question of what should be taught to civil engineering students regarding computing. The surveys reported in this paper are a follow-up study to the two earlier surveys. Key findings of the study include: (1) the relative importance of the top four skills (spreadsheets, word processors, computer aided-design, electronic communication) has remained unchanged; (2) programming competence is ranked very low by practitioners; (3) the importance and use of geographic information system and specialized engineering software have increased over the past decade; (4) the importance and use of expert systems have significantly decreased over the past decade; and (5) the importance and use of equation solvers and databases have declined over the past decade.
While currently numerous existing engineering applications benefit from the global positioning system (GPS), it is anticipated that operation of many new, emerging applications (e.g., applications related to ubiquitous mobile computing) will rely on the information provided by this technology. Depending on the application requirement, GPS data may be collected and post-processed or collected and processed in real time. In either case, there are questions about availability, quality, and reliability of GPS data in engineering applications. To date, despite available techniques for realizing, and to some extent improving, a certain level of GPS accuracy, there is no integrated, coherent approach or technique that would provide users with solutions that combine GPS availability, quality, and reliability. To that end, we propose quality of service (QoS) assurance for GPS. With GPS QoS, users and applications would be provided with the means for predicting GPS solutions in advance meeting the requirements in a timely and cost-effective manner. We have developed a framework for the proposed GPS QoS called GPSLoc. In this paper, we discuss the requirements, methodologies, models, and algorithms for the GPSLoc framework and the experimentation with one of the GPS QoS parameters (visibility).
This paper reports on the development of a new approach for simulating the thermal behavior of buildings that overcome the limitations of conventional heat-transfer simulation methods such as the finite difference method and the finite element method. The proposed technique uses a coarse-grain approach to model development whereby each element represents a complete building component such as a wall, internal space, or floor. The thermal behavior of each coarse-grain element is captured using empirical modeling techniques such as artificial neural networks (ANNs). The main advantages of the approach compared to conventional simulation methods are (1) simplified model construction for the end-user; (2) simplified model reconfiguration; (3) significantly faster simulation runs (orders of magnitude faster for two- and three-dimensional models); and (4) potentially more accurate results. The paper demonstrates the viability of the approach through a number of experiments with a model of a composite wall. The approach is shown to be able to sustain highly accurate long-term simulation runs, if the coarse-grain modeling elements are implemented as ANNs. In contrast, an implementation of the coarse-grain elements using a linear model is shown to function inaccurately and erratically. The paper concludes with an identification of on-going work and future areas for development of the technique.
Bridge engineers need to group bridges to determine adequate let projects based on their proximities, types of work, costs, and cost constraints for each clustered let project after bridges to be treated yearly are identified. This process is time-consuming and typically performed manually. First, this paper presents the formulation of a bridge clustering problem for determining let projects by considering the bridge proximity and type of work with preference membership functions to simulate the actual decision-making process. Second, a constrained fuzzy c-mean (FCM) clustering algorithm is presented to resolves this problem. A case study using the subset of bridges in the state of Georgia with the hypothetical treatments and costs was used to test the developed algorithm and to demonstrate its capability. The results show that the developed constrained FCM clustering algorithm can, in seconds, effectively determine adequate let projects by clustering bridges while meeting cost constraints. The presented formulation also allows incorporation of additional factors such as preference of clustering bridges with the same route number or same route type that are important to other state Departments of Transportation. Finally, conclusions about the benefits and characteristics of the developed algorithm are summarized, and recommendations for future research are discussed.
The concept of object-oriented programming (OOP) has redefined the design and development of large-scale codes worldwide and is now the order of the day in the software industry. Although OOP offers enormous potential in the scientific software business, this innovative programming technique has yet to find a niche in the development of structural engineering software. The present paper is an attempt to highlight the superior programming capability offered by the OOP approach in computer-aided analysis and design of civil engineering structures. The paper presents a brief theoretical background on the important basic and advanced concepts of OOP within the context of structural engineering. The paper explains the relevant fundamentals of object-oriented modeling and design in structural engineering for the orientation of civil engineering professionals who are new to the concept of OOP. The paper provides simple examples of object-oriented programs for elementary structural analysis to illustrate implementation of the OOP paradigm for computational structural analysis. User-code fragments with accompanying commentary are included to provide more detailed directions to structural engineers who wish to adopt the OOP paradigm. The paper also includes a brief review of the evolution that the computational programming paradigm has undergone over the past few decades to cope with the increasing complexity of software. A comparison of currently prevalent programming paradigms is presented to illustrate the relative advantages of OOP for large-scale software applications in structural engineering.
The presented work extends the state-of-the-art of visualizing discrete-event construction simulations in three dimensions (3D). Efficient methods are presented along with a tool, ParticleWorks, that can be used to animate simulated construction processes that involve unstructured, fluid construction materials as resources or byproducts. Common construction processes that involve such fluid materials include placing concrete, dumping dirt, shotcreting, sandblasting, dewatering, water distribution, and inserting slurry. The writers capitalize on a classical computer graphics concept called particle systems to design simple, simulation model-authorable, parametric-text methods that can describe arbitrary volumes of dynamic fluid construction materials in animated 3D virtual construction worlds. These methods can be used to instrument discrete-event simulation models (or other external authoring interfaces) to automatically generate dynamic visualizations of any modeled construction operations that commonly handle and process fluid construction materials.
A transit route network design (TRND) problem for urban bus operation involves the determination of a set of transit routes and the associated frequencies that achieve the desired objective. This can be formulated as an optimization problem of minimizing the total system cost, which is the sum of the operating cost and the generalized travel cost. A review of previous approaches to solve this problem reveals the deficiency of conventional optimization techniques and the suitability of genetic algorithm (GA) based models to handle such combinatorial optimization problems. Since GAs are computationally intensive optimization techniques, their application to large and complex problems is limited. The computational performance of a GA model can be improved by exploiting its inherent parallel nature. Accordingly, two parallel genetic algorithm (PGA) models are proposed in this study. The first is a global parallel virtual machine (PVM) parallel GA model where the fitness evaluation is done concurrently in a parallel processing environment using PVM libraries. The second is a global message passing interface (MPI) parallel GA model where an MPI environment substitutes for the PVM libraries. An existing GA model for TRND for a large city is used as a case study. These models are tested for computation time, speedup, and efficiency. From the study, it is observed that the global PVM model performed better than the other model.
Practical optimization of infrastructure preservation works programming has always posed a computational challenge due to the complexity and scale of the problem. Critical to the process is formulations in which the identity of individual projects is preserved. This requirement leads to exponential growth of solution space, often resulting in an unmanageable process using traditional analytical optimization techniques. In this paper, we propose an evolutionary-based multiyear optimization procedure for solving network level infrastructure works programming problems using a relatively new concept known as the shuffled complex evolution algorithm. A case study problem is analyzed to illustrate the robustness of the technique. The findings show convergence characteristics of the solution and demonstrate that the algorithm is very efficient and consistent in simultaneous consideration of the trade-off among various infrastructure preservation strategies. It is concluded that the robust search capability of the shuffled complex evolution technique is well suited for solving the combinatorial problems in network level infrastructure preservation works programming.
It is normally recognized that information systems (IS) in the construction industry have not been sufficiently used in the era of information. However, so far no serious comprehensive effort has been made to measure the degree of informatization at the industry level. In order to address this problem, in this paper we propose an informatization assessment methodology for the construction industry. An informatization index for the construction industry (IICI) is developed based on specifics of the construction industry. A survey using IICI was conducted among general contractors in Korea, and the results are analyzed in terms of the measure of assessment, IS phases, construction business functions, and size of the firm. It is found that the proposed methodology can provide meaningful indicators that can be used in quantitative comparative assessment from many different perspectives. Details and implications of the case study are briefly presented.
A new semiactive control strategy that combines a neurocontrol system with a smart damper is proposed to reduce seismic responses of structures. In the proposed semiactive control system, the improved neurocontroller, which was developed by employing a training algorithm based on a cost function and a sensitivity evaluation algorithm to replace an emulator neural network, produces the desired active control force, and then a bang-bang-type controller clips the control forces that cannot be achieved by a smart damper (e.g., a variable orifice damper, controllable fluid damper, etc.). Therefore, the proposed semiactive control strategy is fail-safe in that the bounded-input, bounded-output stability of the controlled structure is guaranteed. Numerical simulation results show that the proposed semiactive control system that employs a neural network-based control algorithm is quite effective in reducing seismic responses.
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