Formalism for Construction Inspection Planning: Requirements and Process Concept

Inspectors currently do not have adequate planning support to prevent inefficient or overlooked inspections and undetected defects. Underlying this problem is the lack of a planning formalism for specifying inspection goals and for developing and selecting inspection plans. This paper discusses the requirements for such a formalism. We describe sources of inspection knowledge and approaches for planning in general and for inspection planning specifically. We then describe a set of requirements for the representation and reasoning needed to support the use of available inspection knowledge to assist inspectors in the processes of creating sets of inspection plan alternatives and reducing that set to a smaller set of inspection plans for a given project.     

Object-Oriented Optimization Approach Using Genetic Algorithms for Lattice Towers

A new approach is presented for the optimization of steel lattice towers by combining genetic algorithms and an object-oriented approach. The purpose of this approach is to eliminate the difficulties in the handling of large size problems such as lattice towers. Improved search and rapid convergence are obtained by considering the lattice tower as a set of small objects and combining these objects into a system. This is possible with serial cantilever structures such as lattice towers. A tower consists of panel objects, which can be classified as separate objects, as they possess an independent property as well as inherent properties. This can considerably reduce the design space of the problem and enhance the result. An optimization approach for the steel lattice tower problem using objects and genetic algorithms is presented here. The paper also describes the algorithm with practical design considerations used for this approach. To demonstrate the approach, a typical tower configuration with practical constraints has been considered for discrete optimization with the new approach and compared with the results of a normal approach in which the full tower is considered.     

Use of GIS and Topology in the Identification and Resolution of Space Conflicts

Construction activities need space on the jobsite for their execution. Workers, equipment, materials, temporary facilities, and the developing structure share the limited jobsite space during the construction period. Multiple types of spaces for different purposes on various locations are required to execute various activities at different times. Hence, space planning helps provide a safe and productive environment. Planners mentally link two-dimensional (2D) drawings and execution schedules to generate dynamic multiple types of space requirements, which is a complex task. Therefore, researchers suggest the use of four-dimensional (4D) modeling and building information modeling (BIM) for space planning. Both simulate the construction process by linking the execution schedule with a three-dimensional (3D) model to visualize the construction sequence in space planning. However, both still lack features such as topography modeling and geospatial analysis, which affect space planning. In this work, 4D geographic information systems (GIS) were used for space planning that facilitates topographic modeling, different types of geospatial analyses, and database management. GIS was also used to generate multiple types of spaces corresponding to various activities. A feature attribute table (FAT) associated with each space describes when, where, and how long that space will be required on the jobsite. GIS-based area topology was implemented through a set of validation rules that define how working areas have to share the jobsite. A GIS-based methodology that enables space planning, time-space conflict identification, and conflict resolution prior to the construction was developed and implemented.     

Robotic Assembly of Space Solar-Power Facilities

This paper profiles research relating to the robotic assembly, inspection, and maintenance of space solar-power facilities. Free-flying robots, fixed-base manipulators, and attached mobile manipulators are examined, the technical challenges facing them are outlined, and their roles in the construction process are illuminated. Themes include autonomous materials delivery, warehousing, large-scale payload handling and mating, payload attachment in confined spaces, and inspection. Research has addressed a fraction of the technologies needed to perform reliable autonomous assembly, inspection, and maintenance. Areas in need of further development are examined and potential research is outlined. Current technology cannot fulfill the requirements of orbital construction. The research and development needed can be completed in the near future, and substantive assembly inspection and maintenance can be achieved.     

Helping clinicians to find data and avoid delays

One major criticism of paper medical records is the time and effort required to find data items or to gain an overview. Computerisation does not necessarily help. To help clinicians find data faster and with less effort, everyone designing and writing in records needs to understand how and why we search records and the design features that make searching easier. This paper describes how clinicians search medical records and how to improve record design, whether on paper or computer, to help clinicians find all the data they need without delay.     

Optimization Research: Enhancing the Robustness of Large-Scale Multiobjective Optimization in Construction

Many construction planning problems require optimizing multiple and conflicting project objectives such as minimizing construction time and cost while maximizing safety, quality, and sustainability. To enable the optimization of these construction problems, a number of research studies focused on developing multiobjective optimization algorithms (MOAs). The robustness of these algorithms needs further research to ensure an efficient and effective optimization of large-scale real-life construction problems. This paper presents a review of current research efforts in the field of construction multiobjective optimization and two case studies that illustrate methods for enhancing the robustness of MOAs. The first case study utilizes a multiobjective genetic algorithm (MOGA) and an analytical optimization algorithm to optimize the planning of postdisaster temporary housing projects. The second case study utilizes a MOGA and parallel computing to optimize the planning of construction resource utilization in large-scale infrastructure projects. The paper also presents practical recommendations based on the main findings of the analyzed case studies to enhance the robustness of multiobjective optimization in construction engineering and management.     

Automated Generation of Work Spaces Required by Construction Activities

To provide a safe and productive environment, project managers need to plan for the work spaces required by construction activities. Work space planning involves representing various types of spaces required by construction activities in three dimensions and across time. Since a construction schedule consists of hundreds of activities requiring multiple types of spaces, it is practically impossible to expect project managers to specify manually the spatiotemporal data necessary to represent work spaces in four dimensions. This paper presents mechanisms that automatically generate project-specific work spaces from a generic work space ontology and a project-specific IFC (industry foundation class) based 4D production model. The generation of these work spaces leads to a space-loaded production model. Within this model, work spaces are represented as being related to the relevant construction activities and methods and as having attributes that describe when, where, and how long they exist, and how much volume they occupy. These space-loaded production models enable richer 4D CAD simulations, time-space conflict analysis, and proactive work space planning prior to construction.     

Forecasting Construction Staffing for Transportation Agencies

When the volume of construction projects let to contract increases significantly, state departments of transportation must critically examine internal construction project management staffing capabilities and accurately forecast the manpower required to execute future projects. This paper describes the development of a model or process to forecast manpower requirements as a function of project type and cost for selected employee classifications. Using data from 130 recently completed highway construction projects and over 11,000 employee payroll entries, regression analysis plots were generated to predict overall manpower requirements for projects of a given type and cost. These overall requirements were then adjusted to predict manpower requirements for individual employee classifications using typical task allocation percentages obtained from questionnaire data. The output from the model serves as input into commercially available critical path method scheduling software to facilitate manpower planning and resource leveling.     

Critical Space Analysis

The construction space scheduling problem has received relatively little attention from researchers and practitioners. We now have sophisticated methods of planning and analyzing the sequence of tasks within the work breakdown structure through time, but the problem of planning where on site those tasks are to be executed is not well-supported especially as those spaces are dynamic as the project progresses. We know that congestion on site reduces output and generates hazards, yet construction planners presently have to rely upon experience and intuition. The research reported here presents a decision support tool for construction project planners to help them address the space scheduling problem. After a review of recent developments in construction space scheduling, the concept of critical space analysis is presented. This forms the basis of decision support tools presented for marking up available space, allocating tasks to spaces, and analyzing and optimizing space loading in relation to the critical path—what we call space-time broking. Requirements capture and evaluation reports from construction planners suggest that the tools presented here have immediate practical relevance. The paper will, therefore, be of interest to both practitioners and researchers.     

Sequence database searches via de novo peptide sequencing by tandem mass spectrometry

A method is described for searching protein sequence databases using tandem mass spectra of tryptic peptides. The approach uses a de novo sequencing algorithm to derive a short list of possible sequence candidates which serve as query sequences in a subsequent homology-based database search routine. The sequencing algorithm employs a graph theory approach similar to previously described sequencing programs. In addition, amino acid composition, peptide sequence tags and incomplete or ambiguous Edman sequence data can be used to aid in the sequence determinations. Although sequencing of peptides from tandem mass spectra is possible, one of the frequently encountered difficulties is that several alternative sequences can be deduced from one spectrum. Most of the alternative sequences, however, are sufficiently similar for a homology-based sequence database search to be possible. Unfortunately, the available protein sequence database search algorithms (e.g. Blast or FASTA) require a single unambiguous sequence as input. Here we describe how the publicly available FASTA computer program was modified in order to search protein databases more effectively in spite of the ambiguities intrinsic in de novo peptide sequencing algorithms.     

QUALICON: Computer-Based System for Construction Quality Management

This paper describes a computer-based system for construction quality management. The system tasks are derived from the elements of ISO 9001 standard and designed to integrate with other computer-aided project management functions. They can assist management in (1) the definition of requirements/criteria for design, construction, and quality management; (2) the development of inspection and test plans; (3) the tracking of actual inspection/test results; (4) the verification of their conformance to defined criteria; (5) the documentation of past experience in the form of standard templates for assisting the tasks involved; and (6) the generation of reports. A model was defined for representing the information used in the system tasks. The central role of the inspection and test plan representation was exploited to associate to construction components and processes, relevant inspections/tests, requirements/criteria, actual results, and nonconformance analyses. Templates were devised to enable the reuse of predefined packages of information, which recur from project to project. The developed system will render the assisted quality management tasks more effective. Its use was tested on data from different construction domains.     

Resource Optimization Using Combined Simulation and Genetic Algorithms

This paper presents a new approach for resource optimization by combining a flow-chart based simulation tool with a powerful genetic optimization procedure. The proposed approach determines the least costly, and most productive, amount of resources that achieve the highest benefit/cost ratio in individual construction operations. To further incorporate resource optimization into construction planning, various genetic algorithms (GA)-optimized simulation models are integrated with commonly used project management software. Accordingly, these models are activated from within the scheduling software to optimize the plan. The result is a hierarchical work-breakdown-structure tied to GA-optimized simulation models. Various optimization experiments with a prototype system on two case studies revealed its ability to optimize resources within the real-life constraints set in the simulation models. The prototype is easy to use and can be used on large size projects. Based on this research, computer simulation and genetic algorithms can be an effective combination with great potential for improving productivity and saving construction time and cost.     

A Follow-the-Leader Approach to Serpentine Robot Motion Planning

Serpentine robots offer advantages over traditional mobile robots and robot arms because they have enhanced flexibility and reachability, especially in convoluted environments. These robots are well suited to inspect large space-fairing truss structures such as the future space station and can also be used to inspect the Space Shuttle cargo bay before launch. Serpentine mechanisms offer unique capabilities on Earth to applications such as bridge inspection, search and rescue, surface coating, and minimally invasive surgery. The work described in this paper will exploit a geometric structure, termed a roadmap, to guide the motions of a serpentine robot in highly convoluted spaces. This approach offers advantages over previous work with serpentine robots because it provides a general mathematical structure that is not mechanism specific, thereby having applications to a large class of problems.     

BCOISOA-BP网络在磨矿粒度软测量中的应用

传统人群搜索(SOA)算法通过计算搜索方向、搜索步长和搜寻更新个体位置三个步骤进行寻优.它的缺点在于计算量大,种群之间信息交流少,导致寻优速度慢.针对人群搜索算法存在的缺点,本文提出二项交叉算子改进人群搜索算法(BCOISOA)对其改进.在计算搜索步长方面,本文采用随机数与最大函数值位置乘积判断子群位置,进而提高全局寻优计算速率.在更新位置方面,本文提出二项交叉算子加强种群之间的联系,避免在更新搜索方向过程中,算法因局部最优而导致过早收敛,进而达到快速、准确寻找最优解的目的.本文将以上二项交叉算子改进人群搜索-BP神经网络算法应用在二段式磨矿过程中,实现磨矿粒度在线软测量.仿真结果表明,与人群搜索算法和粒子群算法进行比较,二项交叉算子改进人群搜索算法收敛速度更快,预测精度最高,满足对磨矿粒度实时检测的要求.     

Urban Freeway Bridge Reconstruction Planning: Case of Mockingbird Bridge

Urban freeway bridge reconstruction is a challenging process. Sites are often located in heavily populated areas and are always congested with traffic and construction activities. Lack of adequate planning on such projects can result in tremendous waste in project cost and schedule, traffic flow efficiency, and most importantly, safety to both the traveling public and construction crews. Accordingly, a need exists to develop techniques to help plan and construct urban bridge projects more effectively. This paper documents the process of replanning a bridge project, Mockingbird Bridge. The case describes a research effort that beneficially applied several construction engineering concepts to the project. For the project, the research resulted in sizable savings in cost and duration. For the industry, the case resulted in several lessons for future projects. Among these, the primary lesson is that the integration of bridge reconstruction sequence, constructability, and traffic control plans is crucial to project success.     

Action Research as a Proactive Research Method for Construction Engineering and Management

Academic research in applied disciplines such as construction engineering and management (CEM) has the dual mission of simultaneously contributing to the solution of practical problems and creating theoretical and conceptual knowledge. To do so, appropriate research approaches are needed. However, extant literature in the field has paid little attention to this issue and research methods used have been almost entirely either quantitative surveys or case studies. In this paper, action research (AR) is proposed as an answer to this knowledge gap. AR aims at building and testing theory within the context of solving an immediate practical problem in a real setting. The paper describes the underlying philosophy and application procedure of AR and highlights its strengths and weaknesses. Then, the applicability of the method to CEM is illustrated through a case study of improving access to information to support planning and decision making in a construction owner organization through designing and implementing a data warehouse. The findings indicate that AR is a reliable, structured, and rigorous research approach that is very useful for conducting applied research in construction and enabling academia to influence and improve construction industry practices. It can also effectively help to improve collaboration between academic researchers and industry practitioners in research and development projects.     

Concentrator utilisation under geological uncertainty

Mineral concentrators are designed from preliminary geological data, and are therefore subject to geological uncertainty. This uncertainty has a demonstrable impact on the mining lifecycle, and has motivated stochastic strategic mine planning algorithms. The current paper describes how these algorithms may be extended to consider mineral processing operations in conjunction with open-pit mining operations. In particular, the paper describes an effective way to incorporate variable concentrator feed grade into these algorithms, which is the first step toward more elaborate representations of mineral concentrators. The resulting framework will be able to connect geological data to alternate configurations of the downstream resources, hence comparing the benefit of each configuration, and the corresponding capital investments. Sample computations are presented, comparing the net present value and utilisation for several different mineral processing capacities.     

Interstitial Space Design in Modern Laboratories

Modern laboratory design and construction is becoming increasingly complex with advancements in mechanical, electrical, plumbing, and specialty system technologies. Laboratory projects often have critical schedules and rigorous maintenance and operations requirements. The use of interstitial spaces that create additional floors for mechanical systems is a design strategy that can facilitate both the construction and operation of laboratories. By providing additional space and easier access to mechanical systems, interstitial designs facilitate maintenance and reconfiguration of laboratories, thus reducing life cycle costs. Despite these and other advantages, the use of interstitial space is often eliminated as a laboratory design option due to perceptions of high first costs. This paper presents an analysis of the advantages and disadvantages of interstitial space design as an alternative to traditional plenum construction. The opinions of experienced operators, designers and builders of interstitial building spaces are presented. Survey results of design and construction professionals are presented illustrating current perceptions (and misconceptions) of interstitial spaces as a design alternative for laboratories. Finally, a detailed interdisciplinary case study redesign is used to illustrate the comprehensive effects of introducing an interstitial space design in an actual modern laboratory in which a 1.6-year payback was achieved on the investment in an interstitial design alternative. The research concludes increased first costs can potentially be offset by savings in construction time, and that valuable savings in maintenance and operation costs help to justify the use of interstitial space design solutions.