Application of lean manufacturing principles to improve a conceptual 238Pu supply process
Not Available
Thomas, Tomcy↗
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Logistical Constraints Must Be Considered in Simulation of Pu-238 Supply Process
ORNL, with support from INL and LANL, is leading a program to restart Pu-238 production in the United States. The development work includes a process simulation component. The process is being modeled using discrete-event system simulation to study the effects of logistical constraints on production rates and other operational characteristics. Vital logistical constraints include nuclear material inventory limits, human resource limitations, equipment capacities, chemical/nuclear behaviors, and quality restrictions.
Sherman, Steven↗
A system of shared autonomous vehicles for Chicago: Understanding the effects of geofencing the service
With autonomous vehicles (AVs) still in the testing phase, researchers and planners must resort to simulation techniques to explore possible futures regarding shared and automated mobility. An agent-based discrete-event transport simulator, POLARIS, is used in this study to simulate travel in the 20-county Chicago region with a shared AV (SAV) mobility option. Using this framework, the effect of an SAV fleet on system performance when constrained to serve within geofences is studied under four distinct scenarios: service restricted to the city, to the city plus suburban core, to the core plus exurban areas, and to the entire region — along with the choice of dynamic ridesharing (DRS) versus solo travel in an SAV. Results indicate that service areas need a balanced mix of trip generators and attractors, and an SAV fleet’s empty VMT (eVMT) can be noticeably reduced through suitable geofencing and DRS. Geofences can also help lower response times, reduce systemwide VMT across all modes, and ensure uniform access to SAVs. DRS is most useful in lowering VMT and %eVMT that arises from sprawled land development, but with insufficient demand to share rides, savings from the use of geofences is higher. Geofences targeting neighborhoods with high trip density bring about low response times and %eVMT, but fleet sizes in these regions need to be designed for uniformly low response times throughout a large region, as opposed to maximizing vehicle use in a 24-hour day.
33 ADVANCED PROPULSION SYSTEMS↗
Supporting Co-Design of Extreme-Scale Systems with In Situ Visual Analysis of Event-Driven Simulations (Final Report)
Extreme-scale systems for compute- and data-centric science are pushing the boundaries of system architectures in order to achieve ambitious goals in terms of computing capability, resilience, and power efficiency. Future systems necessitate emerging designs that incorporate new technologies, system organizations, and computer science techniques, and these changes are not yet well understood. Discrete-event-driven simulation of computing system architectures and subsystems has emerged as a productive and cost-effective means to evaluating potential designs, along with capabilities for executing these simulations of extreme-scale systems. However, techniques for analyzing the behavior of these simulations have not kept pace with our ability to perform the simulations, preventing us from extracting the most value from this promising approach. The objective of this project is to support the codesign of extreme-scale system architectures for compute and data-centric science through research and development of novel methods for analysis and visualization of large-scale event-driven simulations.
97 MATHEMATICS AND COMPUTING↗
Simulation-based Testing of Control Software
It is impossible to adequately test complex software by examining its operation in a physical prototype of the system monitored. Adequate test coverage can require millions of test cases, and the cost of equipment prototypes combined with the real-time constraints of testing with them makes it infeasible to sample more than a small number of these tests. Model based testing seeks to avoid this problem by allowing for large numbers of relatively inexpensive virtual prototypes that operate in simulation time at a speed limited only by the available computing resources. In this report, we describe how a computer system emulator can be used as part of a model based testing environment; specifically, we show that a complete software stack including operating system and application software - can be deployed within a simulated environment, and that these simulations can proceed as fast as possible. To illustrate this approach to model based testing, we describe how it is being used to test several building control systems that act to coordinate air conditioning loads for the purpose of reducing peak demand. These tests involve the use of ADEVS (A Discrete Event System Simulator) and QEMU (Quick Emulator) to host the operational software within the simulation, and a building model developed with the MODELICA programming language using Buildings Library and packaged as an FMU (Functional Mock-up Unit) that serves as the virtual test environment.
97 MATHEMATICS AND COMPUTING↗
Fit Fly: A Case Study of Interconnect Innovation through Parallel Simulation
To meet the demand for exascale-level performance from high-performance computing (HPC) interconnects, many system architects are turning to simulation results for accurate and reliable predictions of the performance of prospective technologies. Testing full-scale networks with a variety of benchmarking tools, including synthetic workloads and application traces, can give crucial insight into what ideas are most promising without needing to physically construct a test network. While flexible, however, this approach is extremely compute time intensive. We address this time complexity challenge through the use of large-scale, optimistic parallel simulation that ultimately leads to faster HPC network architecture innovations. In this paper we demonstrate this innovation capability through a real-world network design case study. Specifically, we have simulated and compared four extreme-scale interconnects: Dragonfly, Megafly, Slim Fly, and a new dual-rail-dual-plane variation of the Slim Fly network topology. We present this new variant of Slim Fly, dubbed Fit Fly, to show how interconnect innovation and evaluation-beyond what is possible through analytic methods-can be achieved through parallel simulation. We validate and compare the model with various network designs using the CODES interconnect simulation framework. By running large-scale simulations in a parallel environment, we are able to quickly generate reliable performance results that can help network designers break ground on the next generation of high-performance network designs.
High Performance Computing↗
Circular Economy Modeling Efforts at NREL: Circular Economy Lifecycle Analysis and Visualization (CELAVI) and the Circular Economy Agent-Based Model (ABM)
Circular Economy (CE) aims at decoupling human activities from economic growth and resource use. While CE economic and environmental benefits are often touted by its proponents, increased circularity and improved sustainability do not necessarily go hand-in-hand. The Circular Economy Lifecycle Assessment and Visualization (CELAVI) framework simulates the transition of renewable energy technology supply chains towards circularity and quantifies spatially explicit environmental impacts and supply chain costs. Using wind blade end-of-life (EOL) management as a case study, this presentation will highlight CELAVI's features. Furthermore, envisioned extension to the framework could improve the stakeholder decision model by accounting for logistical and other factors. The CELAVI framework could be leveraged to answer crucial questions regarding renewables EOL management.
circular economy↗
Hybrid PDES Simulation of HPC Networks Using Zombie Packets
Although high-fidelity network simulations have proven to be reliable and cost-effective tools to peer into architectural questions for high-performance computing (HPC) networks, they incur a high resource cost. The time spent in simulating a single millisecond of network traffic in the highest detail can take hours, even for static, well-behaved traffic patterns such as uniform random. Surrogate models offer a significant reduction in runtime, yet they cannot serve as complete replacements and should only be used when appropriate. Thus, there is a need for hybrid modeling, where high-fidelity simulation and surrogates run side-by-side. Here, we present a surrogate model for HPC networks in which: packets bypass the network, while the network state is left untouched, i.e., suspended. To bypass the network, we use historical data to estimate the arrival time at which every packet should be scheduled at; to suspend the network, all in-flight packets are scheduled to arrive at their destinations, and are kept in the system to awaken as zombies when switching back to high-fidelity. Speedup for a hybrid model is relative to the proportion of surrogate to high-fidelity. This light-weight surrogate obtained up to 76× speedup. Keeping the zombies in the network showed an increase in the accuracy of the high-fidelity simulation on restart when compared to restarting the network from an empty state.
HPC networks↗
A decision support tool for e-waste recycling operations using the hen-and-chicks bio-inspired optimization metaheuristic
E-waste from end-of-life electrical and electronic devices is one of the fastest growing waste streams from households and businesses. E-waste recycling yields environmental sustainability and economic benefits. Due to continuous changes in e-waste types and compositions, recycling businesses face challenges to optimize their operational configuration to achieve better economic and environmental performance. To help e-waste recyclers mitigate this problem, we have developed a modular decision support tool called the Comprehensive Manufacturing Assessment Tool (CMAT) that can simulate both e-waste recycling operations and economics. This tool can give valuable insights regarding the profitability of the entire operation and different e-waste types. In addition, a new bio-inspired metaheuristic optimization algorithm, hen-and-chicks optimization (HACO), was developed to assign manpower to different workstations to maximize operational efficiencies. According to the results of our case study, laptops, desktops, and computer peripherals are the three electronic waste products that produce the most profit. Our examination of the sensitivity of material prices shows that the price of steel has the most significant influence on total profit, because it is the most widely used material in the majority of electronic devices. We have released the decision support tool as open-source software under a general public license. It could be customized for other recycling industries beyond e-waste to achieve business sustainability by making their operations more efficient.
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
The Circular Economy Lifecycle Assessment and Visualization Framework: A Case Study of Wind Blade Circularity in Texas
Moving the current linear economy toward circularity is expected to have environmental, economic, and social impacts. Various modeling methods, including economic input-output modeling, life cycle assessment, agent-based modeling, and system dynamics, have been used to examine circular supply chains and analyze their impacts. This work describes the newly developed Circular Economy Lifecycle Assessment and Visualization (CELAVI) framework, which is designed to model how the impacts of supply chains might change as circularity increases. We first establish the framework with a discussion of modeling capabilities that are needed to capture circularity transitions; these capabilities are based on the fact that supply chains moving toward circularity are dynamic and therefore not at steady state, may encompass multiple industrial sectors or other interdependent supply chains and occupy a large spatial area. To demonstrate the capabilities of CELAVI, we present a case study on end-of-life wind turbine blades in the U.S. state of Texas. Our findings show that depending on exact process costs and transportation distances, mechanical recycling could lead to 69% or more of end-of-life turbine blade mass being kept in circulation rather than being landfilled, with only a 7.1% increase in global warming potential over the linear supply chain. We discuss next steps for framework development.
17 WIND ENERGY↗
LEVERAGING EXISTING TOOLS FOR SIMULATING OPERATOR PERFORMANCE IN DISCRETE DYNAMIC EVENT TREES.
Abstract not provided.
Liao, Huafei↗
LEVERAGING EXISTING TOOLS FOR SIMULATING OPERATOR PERFORMANCE IN DISCRETE DYNAMIC EVENT TREES.
Abstract not provided.
Denman, Matthew R↗
Assessing the Performance of a Circular Economy for Wind Energy Technologies: A Summary of Three Analytical Tools
A circular economy emphasizes the efficient use of all resources and presents opportunities for addressing series of economic and environmental objectives at local, regional, and national levels. Despite anticipated overall benefits to society, the transition to a circular economy is likely to create regional differences in impacts. As a result, it is important to evaluate the performance and tradeoffs associated with circular economy transitions. This poster summaries three previously published analytical tools that were used to assess the performance of developing a circular economy for wind energy technologies: the Renewable Energy Materials Properties Database (REMPD), a circular economy agent-based model for wind blades (CE Wind ABM), and the Circular Economy Lifecycle Assessment and Visualization (CELAVI) framework. The REMPD is a comprehensive database of materials used in wind and solar plants, including material quantities and physical materials availability. The CE Wind ABM allows us to understand how wind stakeholders' end-of-life behaviors influence wind blade circularity and evaluate the impact of regional variables (e.g., logistics and transportation). And, the CELAVI framework is a modular framework that can be used to evaluate the impacts associated with circular economy transitions. These three analytical tools have been applied to evaluate circular economy transitions for wind energy technologies and they could be expanded to other technologies and products.
agent-based modeling↗
WOMBAT Tutorial
This workshop will provide a comprehensive overview to Windfarm Operations and Maintenance cost-Benefit Analysis Tool (WOMBAT), NREL's first wind O&M software model. The session will discuss how to utilize WOMBAT to answer O&M research questions covering land-based, offshore, and distributed wind farms. It will offer an introduction to the model and how it operates. The team will then offer a demonstration of the various modeling parameters by converting the CORE Wind Floating Wind Strategies O&M Assessment assumptions into an analysis-ready configuration, diving into the results, and exploring further model variations.
discrete event simulation↗
TADSim: Discrete Event-based Performance Prediction for Temperature Accelerated Dynamics
Next-generation high-performance computing will require more scalable and flexible performance prediction tools to evaluate software--hardware co-design choices relevant to scientific applications and hardware architectures. Here, we present a new class of tools called application simulators—parameterized fast-running proxies of large-scale scientific applications using parallel discrete event simulation. Parameterized choices for the algorithmic method and hardware options provide a rich space for design exploration and allow us to quickly find well-performing software--hardware combinations. We demonstrate our approach with a TADSim simulator that models the temperature-accelerated dynamics (TAD) method, an algorithmically complex and parameter-rich member of the accelerated molecular dynamics (AMD) family of molecular dynamics methods. The essence of the TAD application is captured without the computational expense and resource usage of the full code. We accomplish this by identifying the time-intensive elements, quantifying algorithm steps in terms of those elements, abstracting them out, and replacing them by the passage of time. We use TADSim to quickly characterize the runtime performance and algorithmic behavior for the otherwise long-running simulation code. We extend TADSim to model algorithm extensions, such as speculative spawning of the compute-bound stages, and predict performance improvements without having to implement such a method. Validation against the actual TAD code shows close agreement for the evolution of an example physical system, a silver surface. Finally, focused parameter scans have allowed us to study algorithm parameter choices over far more scenarios than would be possible with the actual simulation. This has led to interesting performance-related insights and suggested extensions.
97 MATHEMATICS AND COMPUTING↗
DECA: Discrete Event inspired Cellular Automata for grain structure prediction in additive manufacturing
Microstructure largely dictates macroscopic material properties and is strongly affected by processing. Therefore, the simulation of microstructure evolution in response to thermal fields during processing is of significant interest within the computational materials science community. Additive manufacturing (AM) has emerged as a technique for producing complex geometries and unique microstructures. Yet, complex and rapid thermal cycles in AM pose computational challenges for existing microstructure models. This work proposes a discrete event inspired cellular automata (CA) approach, titled DECA, to accelerate simulation of grain structure evolution in AM. In contrast to conventional time-stepped CA models, this model directly solves the times capture events would take place allowing for stepping in events rather than time (a technique also found in the field of discrete-event simulation). In comparison to purely serial discrete-event models, DECA allows for temporary violation of the causality constraint, but detects and corrects these violations, leading to an emergent phenomenon dubbed causality rippling, in which previously calculated capture events are overwritten. The amount of repeated calculations, defined by the capture ratio, is taken as a measure of computational inefficiency, and the model parameters that affect this ratio are evaluated. The new DECA approach was found to be more computationally efficient than conventional time-stepped CA models while guaranteeing an accurate solution, which can only be achieved in the conventional models for vanishingly small time steps. Finally, opportunities for parallelization and scaling of the new approach are discussed.
36 MATERIALS SCIENCE↗
Simulation Modeling for Reliable Biomass Supply Chain Design Under Operational Disruptions
Lignocellulosic biomass derived fuels and chemicals are a promising and sustainable supplement for petroleum-based products. Currently, the lignocellulosic biofuel industry relies on a conventional system where feedstock is harvested, baled, stored locally, and then delivered in a low-density format to the biorefinery. However, the conventional supply chain system causes operational disruptions at the biorefinery mainly due to seasonal availability, handling problems, and quality variability in biomass feedstock. Operational disruptions decrease facility uptime, production efficiencies, and increase maintenance costs. For a low-value high-volume product where margins are very tight, system disruptions are especially problematic. In this work we evaluate an advanced system strategy in which a network of biomass processing centers (depots) are utilized for storing and preprocessing biomass into stable, dense, and uniform material to reduce feedstock supply disruptions, and facility downtime in order to boost economic returns to the bioenergy industry. A database centric discrete event supply chain simulation model was developed, and the impact of operational disruptions on supply chain cost, inventory and production levels, farm metrics and facility metrics were evaluated. Three scenarios were evaluated for a 7-year time-period: (1) bale-delivery scenario with biorefinery uptime varying from 20 to 85%; (2) pellet-delivery scenario with depot uptime varying from 20 to 85% and biorefinery uptime at 85%; and (3) pellet-delivery scenario with depot and biorefinery uptime at 85%. In scenarios 1 and 2, tonnage discarded at the field edge could be reduced by increasing uptime at facility, contracting fewer farms at the beginning and subsequently increasing contracts as facility uptime increases, or determining alternative corn stover markets. Harvest cost was the biggest contributor to the average delivered costs and inventory levels were dependent on facility uptimes. We found a cascading effect of failure propagating through the system from depot to biorefinery. Therefore, mitigating risk at a facility level is not enough and conducting a system-level reliability simulation incorporating failure dependencies among subsystems is critical.
09 BIOMASS FUELS↗
V1G Frequency Regulation: Algorithm Development, Validation & Analysis at Scale
Researchers at Argonne National Laboratory developed and validated a high-fidelity digital twin of a smart charging (V1G) ecosystem to model the participation of up to 1,000 unique electric vehicles (EVs) in the PJM frequency regulation market. Utilizing a discrete-event framework, the simulation models complex interactions, from dynamic grid signals (updated every 2 seconds) to individual EV charging dynamics. The simulation incorporates multiple EV models created from real-world lab test data. Researchers tested multiple control algorithms to balance the dual objectives of maximizing aggregator’s revenue and driver charging needs. Results demonstrate that aggregated EVs function as a controllable, highly effective grid resource, achieving high PJM Performance Scores (80–90%). Additionally, an optimized, market-aware bidding strategy was identified as key to profitability. The platform was shown to provide drivers with an average charging discount of nearly 50%. The algorithm was further validated in the lab using production EVs and charging stations to compare simulation results with real-world performance.
Manne, Nithin↗