Results for “User Behavior” — Page 26

DOE OSTI2021

RouteE: A Vehicle Energy Consumption Prediction Engine

The emergence of connected and automated vehicles and smart cities technologies create the opportunity for new mobility modes and routing decision tools, among many others. To achieve maximum mobility and minimum energy consumption, it is critical to understand the energy cost of decisions and optimize accordingly. The Route Energy prediction model (RouteE) enables accurate estimation of energy consumption for a variety of vehicle types over trips or sub-trips where detailed drive cycle data are unavailable. Applications include vehicle route selection, energy accounting and optimization in transportation simulation, and corridor energy analyses, among others. The software is a Python package that includes a variety of pre-trained models from the National Renewable Energy Laboratory (NREL). However, RouteE also enables users to train custom models using their own data sets, making it a robust and valuable tool for both fast calculations and rigorous, data-rich research efforts. The pre-trained RouteE models are established using NREL's Future Automotive Systems Technology Simulator paired with approximately 1 million miles of drive cycle data from the Transportation Secure Data Center, resulting in energy consumption behavior estimates over a representative sample of driving conditions for the United States. Validations have been performed using on-road fuel consumption data for conventional and electrified vehicle powertrains. Transferring the results of the on-road validation to a larger set of real-world origin-destination pairs, it is estimated that implementing the present methodology in a green-routing application would accurately select the route that consumes the least fuel 90% of the time. The novel machine learning techniques used in RouteE make it a flexible and robust tool for a variety of transportation applications.

47 OTHER INSTRUMENTATION↗

DOE OSTI2026

EVI-X Electric Vehicle Infrastructure Toolbox

The Electric Vehicle Infrastructure Toolbox offers resources for estimating charging infrastructure needs and associated electrical demands based on user-defined electric vehicle adoption scenarios. For more information and additional resources, see the full EVI-X modeling suite of electric vehicle charging infrastructure analysis tools.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2023

Opinions from Users Across the Lifespan about Fully Autonomous and Rideshare Vehicles with Associated Features

Fully autonomous vehicles have the potential to fundamentally transform the future transportation system. While previous research has examined individuals’ perceptions towards fully autonomous vehicles, a complete understanding of attitudes and opinions across the lifespan is unknown. Therefore, individuals’ awareness, acceptance, and preferences towards autonomous vehicles were obtained from 75 participants through interviews with three diverse groups of participants: 20 automotive engineering graduate students who were building an autonomous concept vehicle, 21 non-technical adults, and 34 senior citizens. The results showed that regardless of age, an individual’s readiness to ride in a fully autonomous vehicle and the vehicle’s requirements were influenced by the users’ understanding of autonomous vehicles. All of the engineering students understand what a fully autonomous vehicle is and this group was the most willing to ride especially compared to the seniors, where only half of the seniors knew what a fully autonomous vehicle is and 58.8% were not at all ready to ride one. The desire to have a manual control option or the ability to override the vehicle was common (90% of the engineering students, 95.2% of the adults, and 82.4% of the seniors), especially for individuals who reported not being ready to ride in a fully autonomous vehicle. The majority of all three groups of participants (85% of the engineering students, 81% of the adults, and 52.9% of the seniors) considered it essential that the vehicle should convey information about the vehicle’s status and intended behavior. Diagnostic information about the vehicle was desired by the engineering students (71.4%), who had a technical understanding of autonomous vehicles and current automotive related technologies. When autonomous vehicles are available, most participants anticipate preferring to use them as a rideshare service model (75% of the engineering students, 38% of the adults, and 27% of the seniors) rather than owning (5% of the engineering students, 19% of the adults, and 21% of the seniors) the autonomous vehicle themselves. Regarding the topic of sharing rides with strangers, both the automotive engineering students (90%) and the adults (52.6%) were comfortable with the idea of pooled rideshare in comparison to the seniors (29.4%). In future efforts, it will be important to include potential autonomous vehicle users of a wide age range as well as physical, cognitive, and visual abilities.

Gangadharaiah, Rakesh↗

DOE OSTI2020

Advancing Diagnostic Model Evaluation to Better Understand Water Shortage Mechanisms in Institutionally Complex River Basins

Abstract Water resources systems models enable valuable inferences on consequential system stressors by representing both the geophysical processes determining the movement of water and the human elements distributing it to its various competing uses. This study contributes a diagnostic evaluation framework that pairs exploratory modeling with global sensitivity analysis to enhance our ability to make inferences on water scarcity vulnerabilities in institutionally complex river basins. Diagnostic evaluation of models representing institutionally complex river basins with many stakeholders poses significant challenges. First, it needs to exploit a large and diverse suite of simulations to capture important human‐natural system interactions as well as institutionally aware behavioral mechanisms. Second, it needs to have performance metrics that are consequential and draw on decision‐relevant model outputs that adequately capture the multisector concerns that emerge from diverse basin stakeholders. We demonstrate the proposed model diagnostic framework by evaluating how potential interactions between changing hydrologic conditions and human demands influence the frequencies and durations of water shortages of varying magnitudes experienced by hundreds of users in a subbasin of the Colorado River. We show that the dominant factors shaping these effects vary both across users and, for an individual user, across percentiles of shortage magnitude. These differences hold even for users sharing diversion locations, demand levels or water right seniority. Our findings underline the importance of detailed institutional representation for such basins, as institutions strongly shape how dominant factors of stakeholder vulnerabilities propagate through the complex network of users.

Hadjimichael, Antonia↗

DOE OSTI2013

VARI3D & PERSENT: Perturbation and Sensitivity Analysis

The nodal diffusion method is one of the most widely used approaches in modern reactor analysis. In the nodal diffusion method, a coarse multi-group set of “homogenized” parameters is constructed such that the complex geometry of a reactor core along with the energy dependence of neutron and gamma ray cross sections in a nuclear reactor are conserved in the simpler geometry. The homogenization is typically done on a fuel assembly level as is the case in the DIF3D code developed at Argonne National Laboratory. The nodal methodology is used primarily to predict fuel cycle behavior of nuclear systems of which there is a substantial amount of validation in the literature. Another use of the nodal method is to obtain reactivity coefficients and kinetics parameters for use in a safety analysis of a given nuclear reactor. While there are many ways to obtain reactivity worth and kinetics parameters, the work presented in this manuscript is unique as it provides the user with the ability to compute reactivity worths, kinetics parameters, and cross section sensitivities with a Cartesian and hexagonal geometry based transport code. This manuscript serves as a single manual for two separate codes: VARI3D and PERSENT. The VARI3D code (VARiational 3D) is based upon the classic finite difference diffusion theory solver available in DIF3D. The PERSENT code (PERturbation and SENitivity for Transport) is based upon the variational nodal method employed in DIF3D termed VARIANT. The VARIANT solver was added to DIF3D in 1995 and has seen continued development and use for the last 18 years. Because VARI3D primarily uses deprecated coding practices, rather than incorporate the perturbation and sensitivity treatments for transport within VARI3D, a new coding development was built using modern Fortran coding. The primary purpose of this manual is to describe the theory behind PERSENT (and by convenience, that of VARI3D) and discuss the input and output of PERSENT along with giving potential users an idea of how to use it. While this manuscript does describe the input and output of VARI3D, the PERSENT code is intended to be the replacement capability of VARI3D as PERSENT can generate nearly identical (if not superior) diffusion theory results. In this manuscript, the relevant aspects of generalized perturbation theory that are relevant to both VARI3D and PERSENT are covered. The input and output of VARI3D is displayed by excerpting several of the example problems. Similarly, the input and output of PERSENT is displayed along with tips on how best to use the code. Note that the input and output of the inhomogeneous solver wrapped around DIF3D (DIF3D_IFS) is also discussed as it is needed to carry out some of the sensitivities in PERSENT such as reaction rate ratios. This manuscript describes several perturbation theory problems and sensitivity problems and the results computed using PERSENT. From these sections, potential users should find that PERSENT provides not only the typical tables of numbers desired in perturbation and sensitivity analysis work, but also can visually plot the result for a more thorough understanding of the space and energy distribution (Section 5). Overall, PERSENT is observed to produce accurate reactivity worths and sensitivities for the displayed set of test problems and clearly demonstrates the need to have a transport based sensitivity capability as evident from the thousands of percent errors observed in the 21 group hexagonal fast reactor problem (covered in Section 7).

Smith, M. A.↗

DOE OSTI2018

VARI3D & PERSENT: Perturbation and Sensitivity Analysis

The nodal diffusion method is one of the most widely used approaches in modern reactor analysis. In the nodal diffusion method, a coarse multi-group set of “homogenized” parameters is constructed such that the complex geometry of a reactor core along with the energy dependence of neutron and gamma ray cross sections in a nuclear reactor are conserved in the simpler geometry. The homogenization is typically done on a fuel assembly level as is the case in the DIF3D code developed at Argonne National Laboratory. The nodal methodology is used primarily to predict fuel cycle behavior of nuclear systems of which there is a substantial amount of validation in the literature. Another use of the nodal method is to obtain reactivity coefficients and kinetics parameters for use in a safety analysis of a given nuclear reactor. While there are many ways to obtain reactivity worth and kinetics parameters, the work presented in this manuscript is unique as it provides the user with the ability to compute reactivity worths, kinetics parameters, and cross section sensitivities with a Cartesian and hexagonal geometry based transport code.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2020

VARI3D & PERSENT: Perturbation and Sensitivity Analysis

The nodal diffusion method is one of the most widely used approaches in modern reactor analysis. In the nodal diffusion method, a coarse multi-group set of “homogenized” parameters is constructed such that the complex geometry of a reactor core along with the energy dependence of neutron and gamma ray cross sections in a nuclear reactor are conserved in the simpler geometry. The homogenization is typically done on a fuel assembly level as is the case in the DIF3D code developed at Argonne National Laboratory. The nodal methodology is used primarily to predict fuel cycle behavior of nuclear systems of which there is a substantial amount of validation in the literature. Another use of the nodal method is to obtain reactivity coefficients and kinetics parameters for use in a safety analysis of a given nuclear reactor. While there are many ways to obtain reactivity worth and kinetics parameters, the work presented in this manuscript is unique as it provides the user with the ability to compute reactivity worths, kinetics parameters, and cross section sensitivities with a Cartesian and hexagonal geometry based transport code.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2020

VARI3D & PERSENT: Perturbation and Sensitivity Analysis

The nodal diffusion method is one of the most widely used approaches in modern reactor analysis. In the nodal diffusion method, a coarse multi-group set of “homogenized” parameters is constructed such that the complex geometry of a reactor core along with the energy dependence of neutron and gamma ray cross sections in a nuclear reactor are conserved in the simpler geometry. The homogenization is typically done on a fuel assembly level as is the case in the DIF3D code developed at Argonne National Laboratory. The nodal methodology is used primarily to predict fuel cycle behavior of nuclear systems of which there is a substantial amount of validation in the literature. Another use of the nodal method is to obtain reactivity coefficients and kinetics parameters for use in a safety analysis of a given nuclear reactor. While there are many ways to obtain reactivity worth and kinetics parameters, the work presented in this manuscript is unique as it provides the user with the ability to compute reactivity worths, kinetics parameters, and cross section sensitivities with a Cartesian and hexagonal geometry based transport code.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2024

VARI3D & PERSENT: Perturbation and Sensitivity Analysis (Revision 5)

The nodal diffusion method is one of the most widely used approaches in modern reactor analysis. In the nodal diffusion method, a coarse multi-group set of “homogenized” parameters is constructed such that the complex geometry of a reactor core along with the energy dependence of neutron and gamma ray cross sections in a nuclear reactor are conserved in the simpler geometry. The homogenization is typically done on a fuel assembly level as is the case in the DIF3D code developed at Argonne National Laboratory. The nodal methodology is used primarily to predict fuel cycle behavior of nuclear systems of which there is a substantial amount of validation in the literature. Another use of the nodal method is to obtain reactivity coefficients and kinetics parameters for use in a safety analysis of a given nuclear reactor. While there are many ways to obtain reactivity worth and kinetics parameters, the work presented in this manuscript is unique as it provides the user with the ability to compute reactivity worths, kinetics parameters, and cross section sensitivities with a Cartesian and hexagonal geometry-based transport code.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2025

VARI3D & PERSENT: Perturbation and Sensitivity Analysis

The nodal diffusion method is one of the most widely used approaches in modern reactor analysis. In the nodal diffusion method, a coarse multi-group set of “homogenized” parameters is constructed such that the complex geometry of a reactor core along with the energy dependence of neutron and gamma ray cross sections in a nuclear reactor are conserved in the simpler geometry. The homogenization is typically done on a fuel assembly level as is the case in the DIF3D code developed at Argonne National Laboratory. The nodal methodology is used primarily to predict fuel cycle behavior of nuclear systems of which there is a substantial amount of validation in the literature. Another use of the nodal method is to obtain reactivity coefficients and kinetics parameters for use in a safety analysis of a given nuclear reactor. While there are many ways to obtain reactivity worth and kinetics parameters, the work presented in this manuscript is unique as it provides the user with the ability to compute reactivity worths, kinetics parameters, and cross section sensitivities with a Cartesian and hexagonal geometry based transport code. This manuscript serves as a single manual for two separate codes: VARI3D and PERSENT. The VARI3D code (VARIational 3D) is based upon the classic finite difference diffusion theory solver available in DIF3D. The PERSENT code (PERturbation and SENitivity for Transport) is based upon the variational nodal method employed in DIF3D termed VARIANT. The VARIANT solver was added to DIF3D in 1995 and has seen continued development and use for the last 18 years. Because VARI3D primarily uses deprecated coding practices, rather than incorporating the perturbation and sensitivity treatments for transport within VARI3D, a new coding development was built using modern Fortran coding. The primary purpose of this manual is to describe the theory behind PERSENT (and by convenience, that of VARI3D) and discuss the input and output of PERSENT along with giving potential users an idea of how to use it. While this manuscript does describe the input and output of VARI3D, the PERSENT code is intended to be the replacement capability of VARI3D as PERSENT can generate nearly identical (if not superior) diffusion theory results. In this manuscript, the relevant aspects of generalized perturbation theory and exact perturbation theory that apply to both VARI3D and PERSENT are covered. The input and output of VARI3D is displayed by excerpting several of the example problems. Similarly, the input and output of PERSENT is displayed along with tips on how best to use the code. Note that the input and output of the inhomogeneous solver wrapped around DIF3D (DIF3D_IFS) is also discussed as it is needed to carry out some of the sensitivities in PERSENT such as reaction rate ratios. This manuscript describes several perturbation and sensitivity problems, and the results computed using PERSENT. From these sections, potential users should find that PERSENT provides not only the typical tables of numbers desired in perturbation and sensitivity analysis work, but also can visually plot the result for a more thorough understanding of the space and energy distribution (Section 5). Overall, PERSENT is observed to produce accurate reactivity worths and sensitivities for the displayed set of test problems and clearly demonstrates the need to have a transport-based sensitivity capability as evident from the thousands of percent errors observed in the 21-group hexagonal fast reactor problem (covered in Section 7). The uncertainty calculation capability is described in Section 3 and demonstrated in Section 7.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2013

DISFRAC Version 2.0 Users Guide

DISFRAC is the implementation of a theoretical, multi-scale model for the prediction of fracture toughness in the ductile-to-brittle transition temperature (DBTT) region of ferritic steels. Empirically-derived models of the DBTT region cannot legitimately be extrapolated beyond the range of existing fracture toughness data. DISFRAC requires only tensile properties and microstructural information as input, and thus allows for a wider range of application than empirical, toughness data dependent models. DISFRAC is also a framework for investigating the roles of various microstructural and macroscopic effects on fracture behavior, including carbide particle sizes, grain sizes, strain rates, and material condition. DISFRAC s novel approach is to assess the interaction effects of macroscopic conditions (geometry, loading conditions) with variable microstructural features on cleavage crack initiation and propagation. The model addresses all stages of the fracture process, from microcrack initiation within a carbide particle, to propagation of that crack through grains and across grain boundaries, finally to catastrophic failure of the material. The DISFRAC procedure repeatedly performs a deterministic analysis of microcrack initiation and propagation within a macroscopic crack plastic zone to calculate a critical fracture toughness value for each microstructural geometry set. The current version of DISFRAC, version 2.0, is a research code for developing and testing models related to cleavage fracture and transition toughness. The various models and computations have evolved significantly over the course of development and are expected to continue to evolve as testing and data collection continue. This document serves as a guide to the usage and theoretical foundations of DISFRAC v2.0. Feedback is welcomed and encouraged.

Cochran, Kristine B.↗

DOE OSTI2022

What is the Right Size for a Residential Building Parcel Locker?

Common-carrier parcel lockers present a solution for decreasing delivery times, traffic congestion, and emissions in dense urban areas through consolidation of deliveries. Multi-story residential buildings with large number of residents, and thus a high volume of online package orders, are one of the best venues for installing parcel lockers. But what is the right size for a residential building locker that would suit the residents’ and building managers’ needs? Because of the novelty of parcel lockers, there is no clear guideline for determining the right locker size and configuration for a residential building given the resident population. A small locker would result in packages exceeding capacity and being left in the lobby, increasing the building manager’s workload and confusing and inconveniencing users. On the other hand, a large locker is more expensive, more difficult to install, and unappealing to residents. To answer this question, we installed a common-carrier parcel locker in a residential building in downtown Seattle, WA, U.S.A. Through collecting detailed data on locker usage from the locker provider company, we studied and quantified carriers’ delivery patterns and residents’ online shopping and package pickup behaviors. We then used this information to model the locker delivery and pickup process, and simulated several locker configurations to find the one that best suits the delivery needs of the building. These findings could aid urban planners and building managers in choosing the right size for residential building lockers that meet delivery demand while minimizing costs and contributing to environmental benefits.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2023

Energy Characterization of the UMD Electron Accelerator

Multiple different groups at Los Alamos National Laboratory have a cited interest in understanding the effects of ionizing radiation in materials. Of especial interest to the ISR division is understanding the effects in materials that are used in the space environment, where radiation is omnipresent and impossible to fully shield from. Development is under way to simulate the effects of radiation damage in detectors and electronics, primarily with particle transport codes such as Geant4 and RAMPART, a code that provides a user friendly interface to Geant4. However, these simulations need benchmarking to experimental tests, some of which have been performed at a variety of small electron accelerator facilities. One of these facilities is the Linear Electron Accelerator at the University of Maryland Radiation Facilities. This facility can provide electron beams on the order of 100 mA delivered in tight macropulse bunches, which allows for experiments where the behavior of electronics is monitored as a function of pulse number. While the beam rates per macropulse of this accelerator is monitored during an experiment via a current pick-off connected to a large graphite beamstop, the energy distribution of this electron beam is not measured during the experiment and has not been well characterized. The energy distribution of the beam is pertinent for these types of experiments, since dose is directly related to energy deposited in a medium. Further, these experiments are performed in open air and sample placement in the room can dictate what dose rate they receive per macropulse. We have created simulated dosemaps for the UMD vault room, but these simulations assume a given energy of the beam, both for calculating the dose and to simulate how much the beam diverges in the air. There have been two attempts now to characterize this accelerator beam energy with a plate type spectrometer, including the most recent experiment earlier this year to quantify the beam energy distribution. These results will also be compared to a dosimetry experiment performed by collaborators at the UMD facility, the details of which are described in Reference. Understanding the electron beam energy is important for future experiments, because the energy directly impacts the dose and radiation damage given to a sample and is important for properly simulating the electron beam when comparing simulation to experiment.

43 PARTICLE ACCELERATORS↗

DOE OSTI2026

ComStock Measure Documentation: High-Efficiency Rooftop Unit

Building on the 3-year End-Use Load Profiles project to calibrate and validate the U.S. Department of Energy's ResStock and ComStock models, this work produces national data sets that enable cities, states, utilities, and other stakeholders to answer a broad range of questions regarding their commercial building stock. ComStock is a highly granular, bottom-up model that uses various data sources, statistical sampling methods, and advanced building energy simulations to estimate the annual subhourly energy consumption of the commercial building stock across the United States. The "baseline" model intends to represent the U.S. commercial building stock as it existed in 2018. The methodology of the baseline model is discussed in the ComStock Reference Documentation. The goal of this work is to develop energy efficiency and demand flexibility measures that cover market-ready technologies and study their mass adoption impact on the baseline building stock. "Measures" refers to various "what-if" scenarios that can be applied to buildings. The results for the baseline and measure scenario simulations are published in public data sets that provide insights into building stock characteristics, operational behaviors, utility bill impacts, and annual and sub-hourly energy usage by fuel type and end use. This report describes the modeling methodology for a single ComStock measure scenario - high-efficiency rooftop unit (RTU) - and briefly introduces key results. The full public data set can be accessed on the Comstock data lake or via the Data Viewer at comstock.nlr.gov. The public data set enables users to create custom aggregations of results for their use case (e.g., filter to a specific county or building type).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2018

Recent Updates to the System Advisor Model (SAM)

The System Advisor Model (SAM) is a mature suite of techno-economic models for many renewable energy technologies that can be downloaded for free as a desktop application or software development kit. SAM is used for system-level modeling, including generating performance pro the release of the code as an open source project on GitHub. Other additions that will be covered include the ability to download data directly into SAM from the National Solar Radiation Database (NSRDB) and up- dates to a user-interface macro that assists with PV system sizing. A brief update on SAM's battery model and its integration with the detailed photovoltaic model will also be discussed. Finally, an outline of planned work for the next year will be presented, including the addition of a bifacial model, support for multiple MPPT inputs for detailed inverter modeling, and the addition of a model for inverter thermal behavior.

14 SOLAR ENERGY↗

DOE OSTI2018

NSUF 2016 Annual Report

The Nuclear Science User Facilities (NSUF) and its partner facilities represent a prototype laboratory that utilizes a distributed partnership, with each facility bringing exceptional capabilities to the relationship including reactors, beamlines, state-of-the-art instruments, hot cells, and equally important, expertise. These capabilities and people together create a nationwide infrastructure that allows the best ideas to be tested using the most advanced capabilities. Through the NSUF, researchers and their collaborators are building on current knowledge to better understand the complex behavior of materials and fuels in a nuclear reactor. The NSUF’s partnership program in 2016 included eight universities, one research and education consortium, three national laboratories, and one industry partner. The avenues opened through these partnerships facilitate cooperative research across the country, matching people with capabilities and students with mentors. The NSUF in 2016 included Idaho National Laboratory (INL) and the following institutions: • Argonne National Laboratory • Center for Advanced Energy Studies (a research and education consortium between Boise State University, INL, Idaho State University, University of Idaho, and University of Wyoming) • Illinois Institute of Technology • Massachusetts Institute of Technology • North Carolina State University • Oak Ridge National Laboratory • Pacific Northwest National Laboratory • Purdue University • University of California, Berkeley • University of Michigan • University of Nevada, Las Vegas • University of Wisconsin • Westinghouse Materials Center of Excellence. This report contains details on new capabilities brought into the NSUF in 2016, the evidence of the increasing research facilitated by the NSUF, and new tools and activities to propel nuclear research and development forward to meet energy reliability and security needs. Learn about the NSUF Nuclear Fuels and Materials Library and the Nuclear Energy Infrastructure Database, and how the robust NSUF website continues to evolve to support new tools. Read about how the NSUF supports Department of Energy (DOE) missions through efforts like the 2016 NSUF Ion Beam Options Workshop, which led to a prioritiza-tion of ion beam facilities according to their ability to support Department of Energy Office of Nuclear Energy (DOE-NE) missions.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2025

Simulation-driven design optimization of reaction injection molding (RIM) process for polydicyclopentadiene (pDCPD): Minimizing cycle time, defects, and warpage

Replacing metal components in trucks, trailers, and buses with lightweight polymer composites is challenging due to high temperatures and complex manufacturing. The Reaction Injection Molding (RIM) process using Dicyclopentadiene (DCPD) resin offers a solution by producing robust parts with excellent stiffness, impact strength, and resistance properties. Simulations are essential for optimizing this process, predicting defects, and improving quality. However, most commercial software is tailored for thermoplastics, requiring thermoset users to generate their own datasets. In this study, a material data card for DCPD was developed to perform RIM simulations. Design of Experiments (DOE) was used to identify key factors affecting filling, curing, and warpage, aiming to minimize cycle time and defects. The simulations explored varying injection gate parameters (size, location, number) and process conditions (mold/resin temperature, injection/curing pressure). Results showed that gate design significantly impacts filling behavior and defects. A single central gate provided balanced flow with fewer defects, while two corner gates led to more defects. Additionally, lower injection pressure increased filling time, while higher mold temperature accelerated curing but led to more warpage. In conclusion, this optimization framework aims to enhance DCPD part performance and promote sustainable manufacturing by reducing waste and energy consumption.

42 ENGINEERING↗

DOE OSTI2025

Enabling Next Generation Reaction Injection Molding (RIM) for Lightweight Structures

Replacing metal components in trucks, trailers, and buses with lightweight polymer composites is challenging due to high temperatures and complex manufacturing. The Reaction Injection Molding (RIM) process using Dicyclopentadiene (DCPD) resin offers a solution by producing robust parts with excellent stiffness, impact strength, and resistance properties. Simulations are essential for optimizing this process, predicting defects, and improving quality. However, most commercial software is tailored for thermoplastics, requiring thermoset users to generate their own datasets. In this project, a material data card for DCPD was developed to perform RIM simulations. Design of Experiments (DOE) was used to identify key factors affecting filling, curing, and warpage, aiming to minimize cycle time and defects. The simulations explored varying injection gate parameters (size, location, number) and process conditions (mold/resin temperature, injection/curing pressure). Results showed that gate design significantly impacts filling behavior and defects. A single central gate provided balanced flow with fewer defects, while two corner gates led to more defects. Additionally, lower injection pressure increased filling time, while higher mold temperature accelerated curing but led to more warpage. This optimization framework aims to enhance DCPD part performance and promote sustainable manufacturing by reducing waste and energy consumption. This research has been performed in collaborations with McClarin Composites. The research outcome has been submitted to the Journal of Manufacturing Processes.

36 MATERIALS SCIENCE↗