Assessing Decision Making Strategies In Construction Management By Using A Schedule-Based Simulation Framework

During the project, managers encounter numerous contingencies and are faced with the challenging task of making decisions that will effectively keep the project on track. This task is very challenging because construction projects are non-prototypical and the processes are irreversible. Therefore, it is critical to apply a methodological approach to develop a few alternative management decision strategies during the planning phase, which can be deployed to manage alternative scenarios resulting from expected and unexpected disruptions in the as-planned schedule. Such a methodology should have the following features but are missing in the existing research: (1) looking at the effects of local decisions on the global project outcomes, (2) studying how a schedule responds to decisions and disruptive events because the risk in a schedule is a function of the decisions made, (3) establishing a method to assess and improve the management decision strategies, and (4) developing project specific decision strategies because each construction project is unique and the lessons from a particular project cannot be easily applied to projects that have different contexts. The objective of this dissertation is to develop a schedule-based simulation framework to design, assess, and improve sequences of decisions for the execution stage. The contribution of this research is the introduction of applying decision strategies to manage a project and the establishment of iterative methodology to continuously assess and improve decision strategies and schedules. The project managers or schedulers can implement the methodology to develop and identify schedules accompanied by suitable decision strategies to manage a project at the planning stage. The developed methodology also lays the foundation for an algorithm towards continuously automatically generating satisfactory schedule and strategies through the construction life of a project. Different from studying isolated daily decisions, the proposed framework introduces the notion of {em decision strategies} to manage construction process. A decision strategy is a sequence of interdependent decisions determined by resource allocation policies such as labor, material, equipment, and space policies. The schedule-based simulation framework consists of two parts, experiment design and result assessment. The core of the experiment design is the establishment of an iterative method to test and improve decision strategies and schedules, which is based on the introduction of decision strategies and the development of a schedule-based simulation testbed. The simulation testbed used is Interactive Construction Decision Making Aid (ICDMA). ICDMA has an emulator to duplicate the construction process that has been previously developed and a random event generator that allows the decision-maker to respond to disruptions in the emulation. It is used to study how the schedule responds to these disruptions and the corresponding decisions made over the duration of the project while accounting for cascading impacts and dependencies between activities. The dissertation is organized into two parts. The first part presents the existing research, identifies the departure points of this work, and develops a schedule-based simulation framework to design, assess, and improve decision strategies. In the second part, the proposed schedule-based simulation framework is applied to investigate specific research problems.

DEVELOPMENT OF AN OPTIMIZATION MODEL FOR BIOFUEL FACILITY SIZE AND LOCATION AND A SIMULATION MODEL FOR DESIGN OF A BIOFUEL SUPPLY CHAIN

A range of societal issues have been caused by fossil fuel consumption in the transportation sector in the United States (U.S.), including health related air pollution, climate change, the dependence on imported oil, and other oil related national security concerns. Biofuels production from various lignocellulosic biomass types such as wood, forest residues, and agriculture residues have the potential to replace a substantial portion of the total fossil fuel consumption. This research focuses on locating biofuel facilities and designing the biofuel supply chain to minimize the overall cost. For this purpose an integrated methodology was proposed by combining the GIS technology with simulation and optimization modeling methods. The GIS based methodology was used as a precursor for selecting biofuel facility locations by employing a series of decision factors. The resulted candidate sites for biofuel production served as inputs for simulation and optimization modeling. As a precursor to simulation or optimization modeling, the GIS-based methodology was used to preselect potential biofuel facility locations for biofuel production from forest biomass. Candidate locations were selected based on a set of evaluation criteria, including: county boundaries, a railroad transportation network, a state/federal road transportation network, water body (rivers, lakes, etc.) dispersion, city and village dispersion, a population census, biomass production, and no co-location with co-fired power plants. The simulation and optimization models were built around key supply activities including biomass harvesting/forwarding, transportation and storage. The built onsite storage served for spring breakup period where road restrictions were in place and truck transportation on certain roads was limited. Both models were evaluated using multiple performance indicators, including cost (consisting of the delivered feedstock cost, and inventory holding cost), energy consumption, and GHG emissions. The impact of energy consumption and GHG emissions were expressed in monetary terms to keep consistent with cost. Compared with the optimization model, the simulation model represents a more dynamic look at a 20-year operation by considering the impacts associated with building inventory at the biorefinery to address the limited availability of biomass feedstock during the spring breakup period. The number of trucks required per day was estimated and the inventory level all year around was tracked. Through the exchange of information across different procedures (harvesting, transportation, and biomass feedstock processing procedures), a smooth flow of biomass from harvesting areas to a biofuel facility was implemented. The optimization model was developed to address issues related to locating multiple biofuel facilities simultaneously. The size of the potential biofuel facility is set up with an upper bound of 50 MGY and a lower bound of 30 MGY. The optimization model is a static, Mathematical Programming Language (MPL)-based application which allows for sensitivity analysis by changing inputs to evaluate different scenarios. It was found that annual biofuel demand and biomass availability impacts the optimal results of biofuel facility locations and sizes.

Technical throughput of material flow systems required to achieve design flow – determined by simulation with aniteration algorithm

This article deals with complex material flow systems and series connections of conveyor and op-erating elements. These can be characterised by a specific availability. The thus resultant overall availabil-ity of necessary “technical throughput” of the individual elements for the achievement of a specified throughput. When the conveyor and operating elements are subjected to a stochastic distribution, the interposition of buffers is necessary but these can also lead to a reduction of the necessary throughput due faults. The system behaviour of complex installations can only be investigated by simulation. The parame-ter changes required in order to achieve specific target values can also be determined by simulation runs in iteration loops.

Simulationsgestütztes Design eines Spritzgieß-Werkzeugeinsatzes mit kontur-angepasster Kühlung

Moderne generische Fertigungsverfahren für innengekühlte Werkzeuge bieten nahezu beliebige Freiheitsgrade zur Gestaltung konturnaher Kühlkanäle. Daraus resultiert ein erhöhter Anspruch an das Werkzeugengineering und die Optimierung der Kühlleistung. Geeignete Simulationsverfahren (wie z.B. Computational Fluid Dynamics - CFD) unterstützen die optimierte Werkzeugauslegung in idealer Weise. Mit der Erstellung virtueller Teststände können Varianten effizient und kostengünstig verglichen und die Kosten für Prototypen und Nacharbeiten reduziert werden. Im Computermodell des Werkzeugs erlauben Soft-Sensoren an beliebiger Position die Überwachung temperatur-kritischer Stellen sowohl im Fluid- als auch im Solidbereich. Der hier durchgeführte Benchmark vergleicht die Performance eines optimierten Werkzeugeinsatzes mit einer konventionellen Kühlung. Die im virtuellen Prozess vorhergesagte Zykluszeitreduzierung steht in guter Übereinstimmung mit realen Experimenten an den ausgeführten Werkzeugen.

Design, Simulation und Erprobung einer aktiven Sitzaufhängung für Nutzfahrzeuge

Nutzfahrzeuge müssen oft durch sehr unebenes Gelände gefahren werden. In diesem Fall wird der Fahrer starken Vibrationen ausgesetzt, die von der Fahrzeugkarosserie durch die Sitzaufhängung auf ihn wirken. Um diese Schwingungen zu verringern, werden die Sitzaufhängungen in der Regel mit Feder-Dämpfer-Systemen ausgerüstet. Jedoch erreichen die passiven Systeme vor allem bei niederfrequenten Schwingungen ihre physikalischen Grenzen. Eine wesentliche Verbesserung des Sitzkomforts kann unter solchen Anregungsbedingungen nur mit einer aktiven Sitzaufhängung erreicht werden. In diesem Beitrag wird ein neuartiges aktives System für die Sitzaufhängung auf Basis von elektrorheologischen Flüssigkeiten vorgestellt. Außerdem werden die theoretischen Grundlagen für die Modellierung der beschriebenen aktiven Sitzaufhängung dargestellt. Anschließend werden die Simulationsergebnisse mit den Messergebnissen unter realen Betriebsbedingungen verglichen. Die Repräsentation der Ergebnisse mit Hilfe der im Bereich der Sitztechnik weit verbreiteten SEAT-Werten (Seat Effective Amplitude Transmissibility) zeigt das Potenzial des entwickelten Systems zur aktiven Reduktion der Schwingungsbelastung des Fahrers und ermöglicht seine objektive Bewertung.

Development of a novel material flow simulation model for the integration of spatial and process relevant information

Simulation techniques are almost indispensable in the analysis of complex systems. Materials- and related information flow processes in logistics often possess such complexity. Further problem arise as the processes change over time and pose a Big Data problem as well. To cope with these issues adaptive simulations are more and more frequently used. This paper presents a few relevant advanced simulation models and intro-duces a novel model structure, which unifies modelling of geometrical relations and time processes. This way the process structure and their geometric relations can be handled in a well understandable and transparent way. Capabilities and applicability of the model is also presented via a demonstrational example.

A Nonstationary Space-Time Gaussian Process Model for Partially Converged Simulations

In the context of expensive numerical experiments, a promising solution for alleviating the computational costs consists of using partially converged simulations instead of exact solutions. The gain in computational time is at the price of precision in the response. This work addresses the issue of fitting a Gaussian process model to partially converged simulation data for further use in prediction. The main challenge consists of the adequate approximation of the error due to partial convergence, which is correlated in both design variables and time directions. Here, we propose fitting a Gaussian process in the joint space of design parameters and computational time. The model is constructed by building a nonstationary covariance kernel that reflects accurately the actual structure of the error. Practical solutions are proposed for solving parameter estimation issues associated with the proposed model. The method is applied to a computational fluid dynamics test case and shows significant improvement in prediction compared to a classical kriging model.

A simulation study of the standard design, the rolling six design, the CRM, and the modified CRM in Phase I clinical trials

The Phase I clinical trial is considered the "first in human" study in medical research to examine the toxicity of a new agent. It determines the maximum tolerable dose (MTD) of a new agent, i.e., the highest dose in which toxicity is still acceptable. Several phase I clinical trial designs have been proposed in the past 30 years. The well known standard method, so called the 3+3 design, is widely accepted by clinicians since it is the easiest to implement and it does not need a statistical calculation. Continual reassessment method (CRM), a design uses Bayesian method, has been rising in popularity in the last two decades. Several variants of the CRM design have also been suggested in numerous statistical literatures. Rolling six is a new method introduced in pediatric oncology in 2008, which claims to shorten the trial duration as compared to the 3+3 design. The goal of the present research was to simulate clinical trials and compare these phase I clinical trial designs. Patient population was created by discrete event simulation (DES) method. The characteristics of the patients were generated by several distributions with the parameters derived from a historical phase I clinical trial data review. Patients were then selected and enrolled in clinical trials, each of which uses the 3+3 design, the rolling six, or the CRM design. Five scenarios of dose-toxicity relationship were used to compare the performance of the phase I clinical trial designs. One thousand trials were simulated per phase I clinical trial design per dose-toxicity scenario. The results showed the rolling six design was not superior to the 3+3 design in terms of trial duration. The time to trial completion was comparable between the rolling six and the 3+3 design. However, they both shorten the duration as compared to the two CRM designs. Both CRMs were superior to the 3+3 design and the rolling six in accuracy of MTD estimation. The 3+3 design and rolling six tended to assign more patients to undesired lower dose levels. The toxicities were slightly greater in the CRMs.^

Modified 3+3 design for phase I clinical trials

Phase I clinical trial is mainly designed to determine the maximum tolerated dose (MTD) of a new drug. Optimization of phase I trial design is crucial to minimize the number of enrolled patients exposed to unsafe dose levels and to provide reliable information to the later phases of clinical trials. Although it has been criticized about its inefficient MTD estimation, nowadays the traditional 3+3 method remains dominant in practice due to its simplicity and conservative estimation. There are many new designs that have been proven to generate more credible MTD estimation, such as the Continual Reassessment Method (CRM). Despite its accepted better performance, the CRM design is still not widely used in real trials. There are several factors that contribute to the difficulties of CRM adaption in practice. First, CRM is not widely accepted by the regulatory agencies such as FDA in terms of safety. It is considered to be less conservative and tend to expose more patients above the MTD level than the traditional design. Second, CRM is relatively complex and not intuitive for the clinicians to fully understand. Third, the CRM method take much more time and need statistical experts and computer programs throughout the trial. The current situation is that the clinicians still tend to follow the trial process that they are comfortable with. This situation is not likely to change in the near future. Based on this situation, we have the motivation to improve the accuracy of MTD selection while follow the procedure of the traditional design to maintain simplicity. We found that in 3+3 method, the dose transition and the MTD determination are relatively independent. Thus we proposed to separate the two stages. The dose transition rule remained the same as 3+3 method. After getting the toxicity information from the dose transition stage, we combined the isotonic transformation to ensure the monotonic increasing order before selecting the optimal MTD. To compare the operating characteristics of the proposed isotonic method and the other designs, we carried out 10,000 simulation trials under different dose setting scenarios to compare the design characteristics of the isotonic modified method with standard 3+3 method, CRM, biased coin design (BC) and k-in-a-row design (KIAW). The isotonic modified method improved MTD estimation of the standard 3+3 in 39 out of 40 scenarios. The improvement is much greater when the target is 0.3 other than 0.25. The modified design is also competitive when comparing with other selected methods. A CRM method performed better in general but was not as stable as the isotonic method throughout the different dose settings. The results demonstrated that our proposed isotonic modified method is not only easily conducted using the same procedure as 3+3 but also outperforms the conventional 3+3 design. It can also be applied to determine MTD for any given TTL. These features make the isotonic modified method of practical value in phase I clinical trials.^

Interactive Graphic Simulation: An Advanced Methodology to Improve the Teaching-Learning Process in Nuclear Engineering Education and Training

Nowadays, computer simulators are becoming basic tools for education and training in many engineering fields. In the nuclear industry, the role of simulation for training of operators of nuclear power plants is also recognized of the utmost relevance. As an example, the International Atomic Energy Agency sponsors the development of nuclear reactor simulators for education, and arranges the supply of such simulation programs. Aware of this, in 2008 Gas Natural Fenosa, a Spanish gas and electric utility that owns and operate nuclear power plants and promotes university education in the nuclear technology field, provided the Department of Nuclear Engineering of Universidad Politécnica de Madrid with the Interactive Graphic Simulator (IGS) of “José Cabrera” (Zorita) nuclear power plant, an industrial facility whose commercial operation ceased definitively in April 2006. It is a state-of-the-art full-scope real-time simulator that was used for training and qualification of the operators of the plant control room, as well as to understand and analyses the plant dynamics, and to develop, qualify and validate its emergency operating procedures.

Simulation model for the study of overhead rail current collector systems dynamics, focused on the design of a new conductor rail

Overhead rigid conductor arrangements for current collection for railway traction have some advantages compared to other, more conventional, energy supply systems. They are simple, robust and easily maintained, not to mention their flexibility as to the required height for installation, which makes them particularly suitable for use in subway infrastructures. Nevertheless, due to the increasing speeds of new vehicles running on modern subway lines, a more efficient design is required for this kind of system. In this paper, the authors present a dynamic analysis of overhead conductor rail systems focused on the design of a new conductor profile with a dynamic behaviour superior to that of the system currently in use. This means that either an increase in running speed can be attained, which at present does not exceed 110 km/h, or an increase in the distance between the rigid catenary supports with the ensuing saving in installation costs. This study has been carried out using simulation techniques. The ANSYS programme has been used for the finite element modelling and the SIMPACK programme for the elastic multibody systems analysis.

Simulation techniques for design of overhead conductor rail lines for speeds over 140 km/h

In overhead conductor rail lines, aluminium beams are usually mounted with support spacing between 8 and 12 meters, to limit the maximum vertical deflection in the center of the span. This small support spacing limits the use of overhead conductor rail to tunnels, therefore it has been used almost exclusively in metropolitan networks, with operation speeds below 110 km/h. Nevertheless, due to the lower cost of maintenance required for this electrification system, some railway administrations are beginning to install it in some tunnels on long-distance lines, requesting higher operation speeds [1]. Some examples are the Barcelona and Madrid suburban networks (Spain), and recent lines in Turkey and Malaysia. In order to adapt the design of the overhead conductor for higher speeds (V > 160 km/h), particular attention must be paid to the geometry of the conductor rail in critical zones as overlaps, crossings and, especially, transitions between conductor rail and conventional catenary, since the use of overhead conductor rail is limited to tunnels, as already mentioned. This paper describes simulation techniques developed in order to take into account these critical zones. Furthermore, some specific simulations results are presented that have been used to analyze and optimizes the geometry of this special zones to get a better current collection quality, in a real suburban network. This paper presents the work undertaken by the Railways Technology Research Centre (CITEF), having over 10 years of experience in railways research [1-4].

Analysis and design of a thrombectomy device by using simulation techniques

Purpose: In this work, we present the analysis, design and optimization of one experimental device recently developed in the UK, called the 'GP' Thrombus Aspiration Device (GPTAD). This device has been designed to remove blood clots without the need to make contact with the clot itself thereby potentially reducing the risk of problems such as downstream embolisation. Method: To obtain the minimum pressure necessary to extract the clot and to optimize the device, we have simulated the performance of the GPTAD analysing the resistances, compliances and inertances effects. We model a range of diameters for the GPTAD considering different forces of adhesion of the blood clot to the artery wall, and different lengths of blood clot. In each case we determine the optimum pressure required to extract the blood clot from the artery using the GPTAD, which is attached at its proximal end to a suction pump. Result: We then compare the results of our mathematical modelling to measurements made in laboratory using plastic tube models of arteries of comparable diameter. We use abattoir porcine blood clots that are extracted using the GPTAD. The suction pressures required for such clot extraction in the plastic tube models compare favourably with those predicted by the mathematical modelling. Discussion & Conclusion: We conclude therefore that the mathematical modelling is a useful technique in predicting the performance of the GPTAD and may potentially be used in optimising the design of the device.