Simulation tool for manpower forecast loading and resource leveling

Traffic congestion is one of the worst problems in many countries. Traffic congestion wastes a huge portion of the national income for fuel and traffic-related environmental and socioeconomic problems. Computer simulation is a powerful tool for analyzing complex and dynamic scenarios. It provides an appealing approach to analyze repetitive processes. Simulation helps decision makers identify different possible options by analyzing enormous amounts of data. Hence, computer simulation can be used effectively to analyze traffic flow patterns and signal light timing. This paper discusses a special-purpose simulation (SPS) tool for optimize traffic signal light timing. The simulation model is capable of optimizing signal light timing at a single junction as well as an actual road network with multiple junctions. It also provides signal light timing for certain time periods according to traffic demand. Traffic engineers at the University of Moratuwa, Sri Lanka are testing the developed tool for actual applications.

Due to increasing U.S. energy demand, the Nuclear Regulatory Commission is currently reviewing permit applications for 25 new nuclear power reactors. However, the previous generation of nuclear plant construction was beset by significant cost and schedule overruns. Several researchers have identified "regulatory ratcheting," increases in retroactive regulations, as one of the primary causes of the poor performance of these projects. Regulatory ratcheting was enabled, in part, by the two step nuclear power plant licensing process (10 CFR Part 50) that required plants under construction to meet all current regulatory requirements before receiving an operating license. This two step licensing process has been replaced by a single step process (10 CFR Part 52). How will this single step licensing process impact project performance? This question is investigated using a dynamic simulation model of the technical and social feedback processes that impact U.S. nuclear plant construction. The research reveals that under 10 CFR Part 52 society's amplified perception of nuclear power risks can still drive regulatory growth leading to potentially significant cost and schedule overruns.

A substantial amount of mining infrastructure projects experience cost and schedule overruns, and this situation is largely brought about by poor requirements management. More specifically, evidence suggests that overruns are primarily due to inadequate requirements definition and scoping, as well as the poor handling of requirements information throughout the project lifecycle.
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\nWith many parallels to mining infrastructure, the construction management literature agrees that there are some common compromising conditions associated with poor requirements management: clients are not fully engaged in the requirements gathering/identifying process; client’s requirements are not properly elicited, identified and captured; decisions made about requirements specifications are solution biased by partisan factions; manual requirements documentation suffers from version control; and the end user’s identification and involvement is usually too late.
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\nOf concern to the mining industry and their infrastructure projects, is that the implications of cost and schedule overruns is significant, to the extent that on average cost overruns can be 95% above the original estimate. This suggests that for the mining industry, overrunning the sanctioned budget and schedule commitments are a regular occurrence. Therefore, the research problem for this study is to the explore requirements management conditions and establish the subsequent contributing factors in mining infrastructure projects that persistently makes them vulnerable to costly overruns.
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\nThis research was divided into two stages, with Study 1 exploring the comprising conditions in requirements management, which subsequently informed Study 2 to establish the contributing factors. This study used semi-structured interviews and some internal documentation reviews to develop a theory to explain why the situation is not improving for mining infrastructure projects. Interview data was collected from a cross-section of professionals currently in owner teams, consulting, and delivering infrastructure projects in the Australian Coal Mining industry. The results of a thematic analysis on interview transcripts finds the claims of the previously identified compromising conditions of construction projects to also be true of mining infrastructure projects, with the additional compromising conditions of ‘late changes to projects by new stakeholders’, which may be peculiar to mining infrastructure projects.
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\nHowever, more pertinently to the development of a theory to explain the situation, a second round of analysis and coding on the transcripts and documentation applied with a Husserlian lens revealed that the requirements management documentation was not fit for purpose, in terms of how it is dominated by exchange-value and fails to adequately capture the use-value and benefits of the project.
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\nThe terms exchange-value is defined as the monetary amount realized at a certain point in time, whereas use-value refers to the specific qualities of the product perceived by customers in relation to their needs, which for example could be functionality. The preferencing of exchange-values is considered a result of the influence of management discourse. This discourse is evident in the requirements documentation that management sanction. However, in the interviews, participants appeared to feel less pressured or bound to adopt the management discourse. As many of them are mining engineers or engineering/mining workers who have
\nmoved into management roles, they tend to speak in terms of use-value (a things ability to satisfy a need) as well as exchange-value (the price or cost of production).
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\nThe findings of this study include the determination of an additional compromising condition to requirements management, which is that of late changes by new stakeholders. Another finding is that a contributing factor to cost and schedule overruns in mining infrastructure projects is the misalignment of values inculcated in requirements management documentation, which privilege the values of management (exchange-value) rather than the values of the client and end-users (use-value).
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\nWhilst these documents and processes are intended to describe, convey, and ultimately safeguard the project’s use-value for the client through to delivery, management is largely the consumers of these documents, and they have unwittingly biased these documents to communicate exchange-value. Furthermore, the exchange-value biased requirements management documentation, influences the processes and discourse around the project, and consequentially marginalizes use-value discourse, which ironically in the long run, drastically increases the cost of the project.

This paper provides an overview of the tools used to conduct independent modeling and simulation of Artemis 1 separation events and highlights challenges and lessons learned across a decade of analysis. An overview of each of the tools along with the process flow and key components of maintaining independence from the Program’s baseline tool set will be provided. In addition, each of the separation analyses conducted will be discussed, making note of key models incorporated for each event and unique challenges that were addressed. The technical work described in this paper is part of an on-going technical assessment conducted by the NASA Engineering and Safety Center to develop and maintain an independent modeling and simulation capability in support of Space Launch System (SLS) and Multi-Purpose Crew Vehicle (MPCV) throughout design, verification, and flight readiness cycles. For Artemis 1, an end-to-end analysis approach was taken with events simulated from launch to re-entry. This paper will focus on the separation events, including liftoff clearance analysis, solid rocket booster (SRB) separation from Core Stage (CS), Service Module (SM) panel jettison, ICPS / Core Stage Separation, and MPCV/ ICPS separation. To assess separation clearances, the NESC has developed a high fidelity, independent 6-degree of freedom (DOF) simulation of the separation events. The simulation was developed using the Program to Optimize Simulated Trajectories II (POST2). POST2 is an industry standard flight trajectory optimization and simulation tool that is Class D compliant and follows NASA NPR 7150.2, which includes regression testing, unit testing, and configuration control of the simulation. The primary objective of the SLS separation and clearance analyses was to estimate the clearances between different vehicle components and/or ground support equipment (GSE) during separation events. The clearance is defined as the minimum distance from any point on one 3D geometry model associated with one vehicle component (or GSE) to any point on another 3D geometry model associated with a vehicle component separating from the main body. The vehicle geometry models used by the NESC to compute the separation clearances were derived from CAD models. POST2 simulation results were post processed in the Exploration Visualization Environment (EVE) tool to compute clearances, and detect recontact occurrences, if any, between the separating stages. EVE is a simulation, visualization, and analysis system designed to integrate time-based dynamics data with detailed graphical models in a full-scale virtual environment. EVE was used to simultaneously calculate more than 30 different separation clearances by “driving” detailed vehicle geometry models with position and attitude time history data obtained from the POST2 simulation. EVE displays each clearance distance visually, at any given instant of time, with a straight line connecting the two closest points on each object and records the time history of the clearance distance in a file. If the clearance reduces to zero, then EVE reports it as a recontact. To perform separation analyses, POST2 Monte Carlo analyses were performed by running 2000 dispersed cases that included over hundreds of uncertainties and dispersions for a range of simulation models including aerodynamics, propulsion, navigation sensors, control actuators, slosh and flexible body dynamics, and winds and atmosphere. Clearances were computed for each of the dispersed Monte Carlo trajectories and overall separation performance was statistically assessed. Over the past decade the POST2 simulation and EVE visualization tools have been used to perform detailed assessments of the separation events that occur during the Artemis 1 ascent. To support these assessments, numerous unique simulation models were developed and integrated into the standard suite of POST2 simulation models to address and resolve key concerns specific to each of the Artemis 1 separation events. In addition to presenting an overview of the multi-body 6-DOF simulation and separation analysis capability, the paper will discuss the integration of key simulation models such as flexible body dynamics, slosh dynamics, separation mechanisms, multi-body aerodynamics, and environmental models. Additional details are provided about other challenges that were addressed, including the use of a convex hull to reduce computational time for clearance calculations, the modeling of incidental recontact during separation events, and the capability to simulate failure scenarios.

This study presents a combined thermal and optical, three-dimensional analysis of an asymmetric compound parabolic collector (ACPC) with an integrated hybrid photovoltaic/thermal (PV/T) receiver with the aim of establishing a sustainable approach in two ways: firstly, by determining the optimal tilt angle for operations, and secondly, by introducing an innovative simulation method which reduces computational cost while calculating thermal performance. Initially the Incident Angle Modifier (IAM) was calculated for a wide range of incident angles, and the ray-tracing results were verified using three different simulation tools (Tonatiuh, COMSOL, and SolidWorks) with mean deviations being lower than 4%. The optimal tilt angle of the collector was determined for seven months of the year by conducting a detailed ray-tracing analysis for the mean day of each month considering whole day operation. In the thermal analysis part, the authors introduced novel numerical modeling for numerical simulations. This modeling method, designed with sustainability in mind, enables lighter computational domains for the air gap while achieving accurate numerical results. The approach was established using two distinct simulation tools: COMSOL and SolidWorks. From the optical analysis, it was found that in all months examined there is a four-hour time range around solar noon in which the optimum tilt angle remains constant at a value of 30°. The numerical models constructed for the thermal analysis were verified with each other (6.15% mean deviation) and validated through experimental results taken from the literature regarding the examined collector (<6% mean deviation). In addition, the two simulation tools exhibited a deviation of around 6% between each other. Finally, the thermal performance of the collector was investigated for the mean day of September at solar noon by adopting the optimal tilt angle for that month according to the optical analysis, considering inlet temperatures from 20 °C up to 80 °C.

Reinforced concrete slabs supported on columns fail by punching when a conical plug of concrete perforates the slab above the column. This failure has been mostly investigated experimentally, so what can numerical simulation contribute to understand this phenomenon? To answer this question, a computational simulation tool based on the finite element method is developed. This numerical model is implemented into a computer code in applying the object-oriented programming concept. The requirements that the numerical model should fulfill are derived from a review of the experimental results published in the literature and obtained in our laboratory. The numerical model reproduces the non-linear material behavior characterizing reinforced concrete structures by decoupling the actions of steel reinforcement and concrete. The steel reinforcement is represented by uniaxial truss elements which follow a bi-linear stress-strain response. The concrete is modeled with continuum elements which are described at the constitutive level within the framework of the incremental flow theory of plasticity. The concrete triaxial strength is delimitated with a new failure criterion. A plastic flow rule is derived so as to reproduce the evolution of the plastic strain observed experimentally. Cracking induces strain-softening which refers to a gradual decrease in tensile strength with increasing deformations. The reduction of the tensile strength is controlled by an isotropic decohesion process which is monitored by constant fracture energy. The stiffness degradation due to cracking is reproduced with an isotropic elastic damage model. A perfect bond between concrete and steel is assumed. The capabilities of the numerical model are illustrated by simulating the localized shear failure in soil under a footing, the uniaxial tensile, and the confined compressive tests in plain and reinforced concrete specimens. The simulation of punching failure is investigated for three circular reinforced concrete slabs. The comparison with experimental results indicates that: (1) the punching failure mechanism –characterized by a localized inclined punching crack– is generated, (2) the value of the punching load is predicted, (3) the cracking sequence is reproduced, (4) the global response is slightly too stiff. For slabs with orthogonal reinforcement, the perfect bond hypothesis does not allow to capture the punching failure mechanism and the numerical model is improved by relaxing this hypothesis. The developed computational simulation tool reproduces the punching failure observed experimentally and is consequently used to investigate the failure mechanism. First, it is shown that the punching crack results from a crack coalescence phenomenon at the top of the slab followed by a crack propagation in the direction of the corner slab-column. Second, a condition for punching failure to occur is determined. Third, it is illustrated that the size-effect observed experimentally is reproduced and is reflected by a modification of the tensile stress distribution along the punching crack. Finally, a parametric study of the punching failure is performed revealing that punching failure is governed by the tensile strength of concrete. It is also shown that increasing the percentage of reinforcement raises the punching load and reduces the ductility of failure. Lastly, the computational simulation tool allows to demonstrate that in a circular slab, the applied bending moment is not determinant for the value of the punching load.

With only half of the carbon footprint of coal, natural gas is widely considered to be an important transition fuel as the world economy shifts away from more carbon-intensive energy sources towards lower-carbon alternatives. Liquefied natural gas (LNG) has accordingly grown as a solution for connecting producers and consumers of this valuable resource that are geographically separated by large distances or barriers that make pipelines infeasible. Many construction projects are underway or being planned around the world to bring onstream the vast amounts of infrastructure required for this strategically important energy source. Despite the importance of these projects, however, they are frequently plagued by significant overruns in both scheduling and cost that could impede the progress of the adoption of natural gas in both the short- and long-term. Towards understanding these impediments, this paper puts forward a systematic literature review that synthesizes project management research and prior contributions in the LNG domain to identify risk factors that are most important to schedule and cost overruns in LNG projects. We then put forward a series of research questions that highlight the most fruitful areas for future investigations in this area, thereby helping to lay the groundwork for research that would potentially speed up the rate at which new natural gas supplies can supplant more carbon intensive fuel sources around the world.

Due to the increasing demand for energy in the United States, the Nuclear Regulatory Commission is currently reviewing permit applications for 26 new nuclear power reactors. However, the previous generation of U.S. civilian nuclear plant construction experienced significant cost and schedule overruns. Previous research identified “regulatory ratcheting” (continuous, retroactive change in nuclear plant regulations) as one of the primary causes of this poor performance. Regulatory ratcheting was enabled by the nuclear industry’s two-step permitting and licensing process for civilian power plant construction, which allowed society’s perception of the risks associated with nuclear plant operation to impact nuclear plant construction. How will public policy and societal risk perception affect the next generation of U.S. civilian nuclear plant construction? This question is investigated using a dynamic simulation model of the public policy and social feedback processes that impact U.S. nuclear plant con...

Even though simulation has been used so far in manufacturing facilities for modelling supply chain management, production management, and business processes, its applications in managing the energy consumption within manufacturing companies represent a new and innovative research domain. This prompted the research undertaken for the work present in this paper. The main focus of this research is to analyse production management in a manufacturing facility and correlate it with the energy consumption. The research initially concentrates on different simulation methodologies and their application in the current manufacturing domain. Literature relating to the correlation of energy consumption with production management has also been reviewed. This review identified very few previous instances where simulation tools were used to predict the energy consumption in a manufacturing facility. This research brings a novel approach to investigating the adaptability of industrial simulation processes and tools for modelling the energy consumption with respect to a variable production output. The end result of this investigation consists of a better understanding of the production system and the energy losses that were captured by the simulation model.

Poor productivity is one of the major challenges facing the oil and gas industry in Australia. This is evidenced by significant cost and schedule overruns on every major LNG development during the recent Australian LNG construction boom. In a world where gas is a global commodity that can be easily exported, the consequences of poor productivity mean that investment dollars are directed overseas to lower risk environments to the detriment of resource development in Australia. This extended abstract explores the causes of poor productivity and it argues that one of the principle reasons is a fragmented contracting strategy, which results in the scope being split among different contractors at various phases of the project lifecycle, requiring complex and often inefficient interface management. This combined with little commercial incentive for contractors to minimise cost for the subsequent phase of the project means the responsibility falls with the operator to optimise costs during the project lifecycle. This extended abstract proposes that BOOM commercial model and contracting strategy is one way to address the productivity challenge. This model incentivises the contractor to engineer to reduce construction cost and to construct to minimise operational and maintenance costs by ensuring the contractor has a significant stake. This better aligns the commercial interests of the contractor and operator. This extended abstract also addresses the types of infrastructure development the model is best suited to and some of the critical success factors required to deliver a successful BOOM outcome.

The paper deals with the design issue of the computer simulation models of the traction inverter reflecting request on the rapid investigation of the efficiency performance under various operational conditions. According to this, a piece-wised linearized simulation tool PLECS is selected for model development, which considers the relevant loss behaviour of the main power circuit semiconductor components. The topologies, for which the simulation models are created, are topologies, one of which is commonly used across the automotive industry as the heart of the traction drive (VSI – Voltage Source Inverter), and its perspective alternative three-level traction inverter topology T-NPC – T-type Neutral Point Clamped. The simulation models created in the given simulation tool are thus subjected to the analysis of power parameters, which also include the calculated power losses of the entire system of semiconductor devices for both topologies of the traction inverter. Based on the obtained power parameters, the efficiency performance under various operational conditions of both topologies is evaluated. The presented methodology enables rapid investigation of operational performance enabling fast optimization methods. Any design of linearized simulation models in the PLECS simulation tool, whose core consists of semiconductor elements, can be analyzed by the proposed methodology.

Computer simulations are routinely conducted to evaluate new statistical methods, to compare the properties among different methods, and to mimic the observed data in genetic epidemiology studies. Conducting simulation studies can become a complicated task as several challenges can occur, such as the selection of an appropriate simulation tool and the specification of parameters in the simulation model. Although abundant simulated data have been generated for human genetic research, currently there is no public database designed specifically as a repository for these simulated data. With the lack of such a database, for similar studies, similar simulations may have been repeated, which resulted in redundant work. Thus, we created an online platform, the Genetic Epidemiology Simulation Database (GESDB), for simulation data sharing and discussion of simulation techniques for genetic epidemiology studies. GESDB consists of a database for storing simulation scripts, simulated data and documentation from published articles as well as a discussion forum, which provides a platform for discussion of the simulated data and exchanging simulation ideas. Moreover, summary statistics such as the simulation tools that are most commonly used and datasets that are most frequently downloaded are provided. The statistics will be informative for researchers to choose an appropriate simulation tool or select a common dataset for method comparisons. GESDB can be accessed at http://gesdb.nhri.org.tw.Database URL:http://gesdb.nhri.org.tw

Computer simulation has emerged as a powerful tool to investigate and design materials without ever making them. Predicting the properties and behavior of materials by computer simulation from the bottom-up perspective has long been a vision of computational materials scientists and, as computational power increases, modeling and simulation tools are becoming crucial to the investigation of material systems. The key to achieving this goal is using hierarchies of paradigms that seamlessly connect quantum mechanics to macroscopic systems. Particular progress has been made in relating molecular-scale chemistry to mesoscopic and macroscopic material properties essential to define the materiome. This chapter reviews large-scale atomistic and coarse-grain modeling methods commonly implemented to investigate the properties and behavior of natural and biological materials with nanostructured hierarchies. We present basic concepts of hierarchical multiscale modeling capable of providing a bottom-up description of chemically complex materials and some example applications related to the study of collagen material at different hierarchical levels.

This study analyzed the historical trends in change orders (COs) associated with the Indiana Department of Transportation (INDOT) highway contracts. It also investigated correlations between COs and base factors (district, project type, contract type, award amount, geographical area (rural vs. urban)), and sought to understand the effect of the root causes but not to predict CO based on root causes. Unlike the base factors, the root causes are unknown prior to construction. The study developed models that forecasted CO characteristics—CO likelihood, CO frequency (count), and CO severity (magnitude) and CO impacts (cost overrun and schedule delay). To address these research questions, the study used INDOT’s 2010–2020 highway contract data involving approximately 5,000 contracts worth just over $10B. The CO trends and patterns (including root causes) were analyzed for five project types at the six highway administrative districts in Indiana. The study identified the base factors that generally have higher propensity to experience more frequent and severe COs and analyzed CO impacts on cost and schedule overruns. The results indicated that 65% of the contracts had at least 1 CO; 30% had at least 5 COs; 10% had at least 12 COs; and 4% had over 20 COs. The study also analyzed the CO impacts by the dominant root causes: changed conditions (9,544 COs, $266M); errors and omissions (6,507 COs, $139M); scope changes (2,371 COs, $109M), and final quantity adjustments (cost adjustment) ($193M). The top five root causes of the COs in each district were identified and good practices and guidelines to help mitigate the incidence and severity of change orders were developed. The study’s diagnostic analysis and prediction models are useful in project planning and management because they (a) help identify the factors that impact CO likelihood, count, and monetary severity, and (b) can enable more reliable forecasting of project cost and schedule. Overall, the study results can help INDOT achieve its strategic goal of “on-time and on-budget project delivery.” The effective management of change orders aligns with specific provisions that recur across previous and current federal legislation (the Infrastructure Investment and Jobs Act), which emphasize efficient project management and adherence to budgets and timelines in infrastructure development.

Plugging the Gaps’ Between Optimum Bias and Strategic Misrepresentation and Infrastructure Cost Overruns