Enabling additive manufacturing part inspection of digital twins via collaborative virtual reality
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42 ENGINEERING↗
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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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Effects of 3D Virtual Simulators in the Introductory Wind Energy Course: A Tool for Teaching Engineering Concepts
Our research provides an innovative solution for optimizing learning effectiveness and improving postsecondary education through the development of virtual simulators that can be easily used and integrated into existing wind energy curriculum. Two 3D virtual simulators are developed in our laboratory for use in an immersive 3D virtual reality (VR) system or for 3D display on a 2D screen. Our goal is to apply these prototypical simulators to train postsecondary students and professionals in wind energy education; and to offer experiential learning opportunities in 3D modeling, simulation, and visualization. The issue of transferring learned concepts to practical applications is a widespread problem in postsecondary education. Related to this issue is a critical demand to educate and train a generation of professionals for the wind energy industry. With initiatives such as the U.S. Department of Energy's “20% Wind Energy by 2030” outlining an exponential increase of wind energy capacity over the coming years, revolutionary educational reform is needed to meet the demand for education in the field of wind energy. These developments and implementation of Virtual Simulators and accompanying curriculum will propel national reforms, meeting the needs of the wind energy industrial movement and addressing broader educational issues that affect a number of disciplines.
29 ENERGY PLANNING, POLICY, AND ECONOMY↗
Development of Digital Twin-Informed Predictive Maintenance for Critical Components in Advanced Reactors
Small modular reactors (SMRs) and microreactors, along with other advanced reactor (AR) technologies, are key to the future of nuclear energy. For these systems to achieve low operating costs, high reliability, and flexibility across applications, their operation and maintenance must be optimized. Digital twin (DT) technology is one of the technologies that enables real-time (or faster than real-time) monitoring and prognosis of critical components which are vital for operational efficiency, low costs, and enhanced safety of ARs, accelerating their deployment. DT technology provides dynamic virtual representation of physical assets by integrating real-time data, physics-based models, and advanced analytics, which is critical to optimizing the performance of the entire energy system throughout the life cycle. DTs empower engineers and operators to virtually explore different scenarios, configurations, and control strategies, allowing for the identification of optimal solutions that maximize reactor efficiency, safety, and economics.
22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
Game-Engine-Assisted Research platform for Scientific computing (GEARS) in Virtual Reality
Not Available
Horton, Brandon K.↗
Release of a High Temperature Engineering Test Reactor (HTTR) Steady-State Multiphysics Model to the Virtual Test Bed
The National Reactor Innovation Center (NRIC) accelerates the demonstration and deployment of advanced nuclear energy through inspiring stakeholders and the public, empowering innovators, and delivering successful outcomes. The Virtual Test Bed (VTB) supports this mission by providing an open-source repository of advanced test reactor models for industry, academia, and the public to utilize. During my time at Idaho National Laboratory (INL), I: • Verified the input files of the High Temperature Engineering Test Reactor • Generated computational results • Created user documentation for the HTTR • Uploaded a steady-state HTTR model to the Virtual Test Bed • Authored a conference publication on the model
22 GENERAL STUDIES OF NUCLEAR REACTORS↗
Pre-Combustion Carbon Capture by a Nanoporous, Superhydrophobic Membrane Contactor Process
This report summarizes progress made during Phase I and Phase II of the project: "Pre-Combustion Carbon Capture by a Nanoporous, Superhydrophobic Membrane Contactor Process," under contract DE-FE-0000646. The objective of this project is to develop a practical and cost effective technology for CO 2 separation and capture for pre-combustion coal-based gasification plants using a membrane contactor/solvent absorption process. The goals of this technology development project are to separate and capture at least 90% of the CO 2 from Integrated Gasification Combined Cycle (IGCC) power plants with less than 10% increase in the cost of energy services. Unlike conventional gas separation membranes, the membrane contactor is a novel gas separation process based on the gas/liquid membrane concept. The membrane contactor is an advanced mass transfer device that operates with liquid on one side of the membrane and gas on the other. The membrane contactor can operate with pressures that are almost the same on both sides of the membrane, whereas the gas separation membranes use the differential pressure across the membrane as driving force for separation. The driving force for separation for the membrane contactor process is the chemical potential difference of CO 2 in the gas phase and in the absorption liquid. This process is thus easily tailored to suit the needs for pre-combustion separation and capture of CO 2 . Gas Technology Institute (GTI) and PoroGen Corporation (PGC) have developed a novel hollow fiber membrane technology that is based on chemically and thermally resistant commercial engineered polymer poly(ether ether ketone) or PEEK. The PEEK membrane material used in the membrane contactor during this technology development program is a high temperature engineered plastic that is virtually non-destructible under the operating conditions encountered in typical gas absorption applications. It can withstand contact with most of the common treating solvents. GTI and PGC have developed a nanoporous and superhydrophobic PEEK-based hollow fiber membrane contactor tailored for the membrane contactor/solvent absorption application for syngas cleanup. The membrane contactor modules were scaled up to 8-inch diameter commercial size modules. We have performing extensive laboratory and bench testing using pure gases, simulated water-gas-shifted (WGS) syngas stream, and a slipstream from a gasification derived syngas from GTI's Flex-Fuel Test Facility (FFTF) gasification plant under commercially relevant conditions. The team have also carried out an engineering and economic analysis of the membrane contactor process to evaluate the economics of this technology and its commercial potential. Our test results have shown that 90% CO 2 capture can be achieved with several physical solvents such as water and chilled methanol. The rate of CO 2 removal by the membrane contactor is in the range of 1.5 to 2.0 kg/m 2 /hr depending on the operating pressures and temperatures and depending on the solvents used. The final economic analysis has shown that the membrane contactor process will cause the cost of electricity to increase by 21% from the base plant without CO 2 capture. The goal of 10% increase in levelized cost of electricity (LCOE) from base DOE Case 1(base plant without capture) is not achieved by using the membrane contactor. However, the 21% increase in LCOE is a substantial improvement as compared with the 31.6% increase in LCOE as in DOE Case 2(state of art capture technology using 2-stages of Selexol TM ).
01 COAL, LIGNITE, AND PEAT↗
Release of a High Temperature Engineering Test Reactor (HTTR) Steady State Multiphysics Model to the Virtual Test Bed
In response to climate change, global governments and private industry have established a common goal of achieving net-zero emissions by 2050 \cite{osti_1865910}. This goal requires a reassessment of current energy demands and production methods. Reducing emissions at an affordable cost while maintaining grid reliability requires a nationwide collaborative effort among government and industry in the United States. Nuclear power is the leading low-carbon electricity generation method. In the past 50 years, the use of nuclear power has reduced carbon dioxide emissions by over 60 gigatons and has played a crucial role in the security of energy supply~\cite{IEA}. In the U.S., nuclear power accounts for 20\% of the electrical supply and provides energy reliably. Advanced reactors will operate at higher temperatures, operate more efficiently, utilize more energy stored within fuel, and reduce the amount of waste produced \cite{osti_1616270}. To face these challenges and goals, the U.S. Department of Energy has created an initiative to focus on the modeling and simulation tools to support future nuclear power plant design, licensing, and operations. The Virtual Test Bed (VTB)~\cite{vtb2023} was launched by the National Reactor Innovation Center (NRIC) in collaboration with the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program to support the advanced nuclear reactor community. The VTB involves teams from both Idaho National Laboratory and Argonne National Laboratory and aims to provide example models for a broad range of both current and future advanced reactor designs. A feature of the VTB is the automatic testing of these models to ensure continued functionality as simulation tools are further developed. The VTB and the advanced reactor models documented there are important resources for this initiative. This work describes the inclusion of a new model on the VTB---a High Temperature Engineering Test Reactor (HTTR) steady-state model \cite{LABOURE2023109838}.
22 GENERAL STUDIES OF NUCLEAR REACTORS↗
Evaluation of Wind Speed Retrieval from Continuous-Wave Lidar Measurements of a Wind Turbine Wake Using Virtual Lidar Techniques
Wind lidar technology is being extensively used in utility-scale wind turbine wake measurements because of its capabilities to capture the dominant structures of interest in the near-wake region. However, wind lidar devices provide only line-of-sight (LOS) measurements, and retrieval of horizontal wind speed from the LOS measurements of a single lidar in the wind turbine wake could introduce errors due to the assumptions used in the retrieval process. With that in mind, the goals of this paper are to estimate the errors associated with the retrieval processes and provide guidelines for best practices. To achieve these goals, virtual lidar samples are obtained with large-eddy simulations (LES) by sampling the flow field with a model of the Technical University of Denmark (DTU) SpinnerLidar. LES is chosen to simulate the neutral and unstable atmospheric boundary layer (ABL), a benchmark case of the International Energy Agency Wind Technology Collaboration Programme (IEA Wind TCP) Task 31. The precursor ABL simulation is validated with the reference data provided by the IEA Wind Task 31 benchmark case. The data from the precursor simulation is used to drive a simulation of a wind turbine submerged in the ABL. A weighting function is applied to the LES data to mimic the real DTU SpinnerLidar measurements. In the end, the virtual lidar data are processed and compared with the original LES data to estimate the errors. Results show that lidar captures mean ABL profile without any noticeable error, whereas turbulence intensity is underpredicted ~15% at hub height for the neutral case. Volume averaging by the lidar technology has a significant effect in the shear layer of a wind turbine wake.
17 WIND ENERGY↗
Cyber-Informed Engineering (CIE) Integration into Model- Based Systems Engineering (MBSE)
Engineering design in the field of industrial engineering, such as designing automated factories or warehouses, is critical for the effective operation of facilities. Any design flaws introduced early can result in significant capital expenses to correct. However, early-stage engineering design is inherently complex. The systems are not yet built, requiring designers to integrate various aspects, including digital engineering and cybersecurity, to support virtual representations throughout the design process. In this study, we propose an approach to integrate Cyber-Informed Engineering (CIE) principles into model-based systems engineering (MBSE). This approach facilitates the development of a digital thread for engineering systems, ensuring secure digital artifacts in the design of industrial engineering systems.
42 - ENGINEERING↗
CO 2 Injection Monitoring with a Scalable, Automated Sparse Seismic Array
Conference presentation at American Institute of Chemical Engineers (AIChE) Annual Meeting, Virtual, November 16–20, 2020. The scalable, automated sparse seismic array (SASSA) method has been ideated as a cost-effective alternative or complementary to conventional 3D seismic methods. Based on a sparse array of receivers deployed strategically on Earth’s surface and one or more fixed seismic sources, the SASSA method can be used to study specific portions of the subsurface to detect the movement of CO 2 in a reservoir with lower environmental footprint and shorter turnaround time to deliver results than conventional 3D seismic methods. Energy & Environmental Research Center (EERC) carried out seismic monitoring of an oilfield undergoing CO 2 enhanced oil recovery in Montana, USA, using the SASSA method.
02 PETROLEUM↗
Software solutions manage the definition, operation, maintenance and configuration control of the National Ignition Facility
The National Ignition Facility (NIF) is the world's largest laser composed of millions of individual parts brought together to form one massive assembly. Maintaining control of the physical definition, status and configuration of this structure is a monumental undertaking yet critical to the validity of the shot experiment data and the safe operation of the facility. The NIF business application suite of software provides the means to effectively manage the definition, build, operation, maintenance and configuration control of all components of the National Ignition Facility. State of the art Computer Aided Design software applications are used to generate a virtual model and assemblies. Engineering bills of material are controlled through the Enterprise Configuration Management System. This data structure is passed to the Enterprise Resource Planning system to create a manufacturing bill of material. Specific parts are serialized then tracked along their entire lifecycle providing visibility to the location and status of optical, target and diagnostic components that are key to assessing pre-shot machine readiness. Nearly forty thousand items requiring preventive, reactive and calibration maintenance are tracked through the System Maintenance & Reliability Tracking application to ensure proper operation. Radiological tracking applications ensure proper stewardship of radiological and hazardous materials and help provide a safe working environment for NIF personnel.
42 ENGINEERING↗
A review of zirconia oxygen, NO x , and mixed potential gas sensors – History and current trends
Zirconia-based electrochemical sensors have revolutionized oxygen monitoring and combustion control. Here, these robust, solid-state devices are found in virtually every internal combustion engine today providing feedback information for tight air to fuel ratio control thus minimizing unwanted emissions and improving engine efficiency. Variations on the sensor design and operational mode enable the measurement of nitrogen oxides to part per million levels, providing control information for exhaust after-treatment systems. Emerging designs include the development of "gas analyzers on a chip" capable of monitoring oxygen, carbon monoxide, nitrogen oxides, ammonia and hydrocarbons.
47 OTHER INSTRUMENTATION↗
Quantifying Volume Change in Porous Electrodes via the Multi-Species, Multi-Reaction Model
Automotive manufacturers are working to improve individual cell and overall pack design by increasing their performance, durability, and range, while reducing cost; and active material volume change is one of the more complex aspects that needs to be considered during this process. As the time from initial design to manufacture of electric vehicles is decreased, design work that used to rely solely on testing needs to be supplemented or replaced by virtual methods. As electrochemical engineers drive battery and system design using model-based methods, the need for coupled electrochemical/mechanical models that take into account the active material change utilizing physics based or semi-empirical approaches is necessary. In this study, we illustrated the applicability of a mechano-electrochemical coupled modeling method considering the multi-species, multi-reaction model as popularized by Verbrugge and Baker. To do this, validation tests were conducted using a computer-controlled press apparatus that can control the press displacement and press force with precision. The coupled MSMR volume change model was developed and its applicability to graphite and NMC cells was illustrated. The increased accuracy of the model considering the coupled MSMR volume change approach shows in the importance of accounting for individual gallery volume change behavior on cell level predictions.
25 ENERGY STORAGE↗
Federal Labs and Research Centers Benefiting California: 2017 Impact Report for State Leaders.
Sandia National Laboratories is the largest of the Department of Energy national laboratories with more than 13,000 staff spread across its two main campuses in New Mexico and California. For more than 60 years, the Sandia National Laboratories campus in Livermore, California has delivered cutting-edge science and technology solutions to resolve the nation’s most challenging and complex problems. As a multidisciplinary laboratory, Sandia draws from virtually every science and engineering discipline to address challenges in energy, homeland security, cybersecurity, climate, and biosecurity. Today, collaboration is vital to ensuring that the Lab stays at the forefront of science and technology innovation. Partnerships with industry, state, and local governments, and California universities help drive innovation and economic growth in the region. Sandia contributed to California’s regional and statewide economy with more than $145 million in contracts to California companies, $92 million of which goes to California small businesses. In addition, Sandia engages the community directly by running robust STEM education programs for local schools and administering community giving programs. Meanwhile, investments like the Livermore Valley Open Campus (LVOC), an innovation hub supported by LLNL and Sandia, help catalyze the local economy.
99 GENERAL AND MISCELLANEOUS↗
Numerical Analysis of Fuel Effects on Advanced Compression Ignition Using a Cooperative Fuel Research Engine Computational Fluid Dynamics Model
Growing environmental concerns and demand for a better fuel economy are driving forces that motivate the research for more advanced engines. Multi-mode combustion strategies have gained attention for their potential to provide high thermal efficiency and low emissions for light-duty applications. These strategies target optimizing the engine performance by correlating different combustion modes to load operating conditions. The extension from boosted spark ignition (SI) mode at high loads to advanced compression ignition (ACI) mode at low loads can be achieved by increasing the compression ratio and utilizing intake air heating. Further, in order to enable an accurate control of intake charge condition for ACI mode and rapid mode-switches, it is essential to gain fundamental insights into the autoignition process. Within the scope of ACI, homogeneous charge compression ignition (HCCI) mode is of significant interest. It is known for its potential benefits, operation at low fuel consumption, low NOx, and particulate matter (PM) emissions. In the present work, a virtual Cooperative Fuel Research (CFR) engine model is used to analyze fuel effects on ACI combustion. In particular, the effect of fuel octane sensitivity (S) (at constant Research Octane Number (RON)) on autoignition propensity is assessed under beyond-RON (BRON) and beyond-MON (BMON) ACI conditions. The three-dimensional CFR engine computational fluid dynamics (CFD) model employs a finite-rate chemistry approach with a multi-zone binning strategy to capture autoignition. Two binary blends with Research Octane Number (RON) of 90 are chosen for this study: primary reference fuel (PRF) with S = 0 and toluene–heptane (TH) blend with S = 10.8, representing paraffinic and aromatic gasoline surrogates. Reduced mechanisms for these blends are generated from a detailed gasoline surrogate kinetic mechanism. Simulation results with the reduced mechanisms are validated against experimental data from an in-house CFR engine, with respect to in-cylinder pressure, heat release rate, and combustion phasing. Thereafter, the sensitivity of combustion behavior to ACI operating condition (BRON versus BMON), air-fuel ratio (λ = 2 and 3), and engine speed (600 and 900 rpm) is analyzed for both fuels. It is shown that the sensitivity of a fuel’s autoignition characteristics to λ and engine speed significantly differs at BRON and BMON conditions. Moreover, this sensitivity is found to vary among fuels, despite the same RON. It is also observed that the presence of low-temperature heat release (LTHR) under BRON condition leads to more sequential autoignition and longer combustion duration than BMON condition. Finally, the study indicates that the octane index (OI) fails to capture the trend in the variation of autoignition propensity with S under the BMON condition.
33 ADVANCED PROPULSION SYSTEMS↗
Optimal decision-making in high-throughput virtual screening pipelines
Screening large pools of molecular candidates to identify those with specific design criteria or targeted properties is demanding in various science and engineering domains. While a high-throughput virtual screening (HTVS) pipeline can provide efficient means to achieving this goal, its design and operation often rely on experts' intuition, potentially resulting in suboptimal performance. In this paper, we fill this critical gap by presenting a systematic framework that can maximize the return on computational investment (ROCI) of such HTVS campaigns. Based on various scenarios, we empirically validate the proposed framework and demonstrate its potential to accelerate scientific discoveries through optimal computational campaigns, especially in the context of virtual screening.
97 MATHEMATICS AND COMPUTING↗
Numerical Investigation of a Central Fuel Property Hypothesis Under Boosted Spark-Ignition Conditions
In the present work, a central fuel property hypothesis (CFPH), which states that fuel properties are sufficient to provide an indication of a fuel’s performance irrespective of its chemical composition, was numerically investigated. In particular, the objective of the study was to determine whether Research Octane Number (RON) and Motor Octane Number (MON), as fuel properties, are sufficient to describe a fuel’s knock-limited performance under boosted spark-ignition (SI) conditions within the framework of CFPH. To this end, four TPRF-bioblendstock surrogates having different compositions but matched RON (=98) and MON (=90), were first generated using a non-linear regression model based on artificial neural network (ANN). Additionally, three unconventional bioblendstocks were included in the analysis: di-isobutylene (DIB), isobutanol, and Anisole. Skeletal reaction mechanisms were generated for the TPRF-DIB, TPRF-isobutanol, and TPRF-anisole blends from a detailed kinetic mechanism. Thereafter, numerical simulations were performed for the fuel surrogates using the skeletal mechanisms and a virtual cooperative fuel research (CFR) engine model, under a representative boosted operating condition. In the computational fluid dynamics (CFD) model, the G-equation approach was employed to track the turbulent flame front and the well-stirred reactor model combined with the multi-zone binning strategy was used to capture auto-ignition in the end-gas. In addition, laminar flame speed (LFS) was tabulated for each blend as a function of pressure, temperature, and equivalence ratio a priori, and the lookup tables were used to prescribe laminar flame speed as an input to the G-equation model. Parametric spark timing sweeps were performed for each fuel blend to determine the corresponding knock-limited spark advance (KLSA) and 50% burn point (CA50) at the respective KLSA timing. It was observed that despite same RON, MON, and engine operating conditions, the TPRF-anisole blend exhibited markedly different knock-limited performance from the other three blends. This deviation from the octane index (OI) expectation was shown to be caused by differences in laminar flame speed. However, it was found that relatively large fuel-specific differences in LFS (>20%) would have to be present to cause any appreciable deviation from the OI framework. Otherwise, RON and MON would still be robust enough to predict a fuel’s knock-limited performance.
42 ENGINEERING↗
Numerical Investigation of a Central Fuel Property Hypothesis under Boosted Spark-ignition Conditions
In the present work, a central fuel property hypothesis (CFPH), which states that fuel properties are sufficient to provide an indication of a fuel's performance irrespective of its chemical composition, was numerically investigated In particular, the objective of the study was to determine whether Research Octane Number (RON) and Motor Octane Number (MON), as fuel properties, are sufficient to describe a fuel's knock-limited performance under boosted spark-ignition (SI) conditions within the framework of CFPH. To this end, four TPRF-bioblendstock surrogates having different compositions but matched RON (= 98) and MON (= 90), were first generated using a non-linear regression model based on artificial neural network (ANN). Three unconventional bioblendstocks were included in the analysis: Di-isobutylene (DIB), Isobutanol and Anisole. Skeletal reaction mechanisms were generated for the TPRF-DIB, TPRF-isobutanol and TPRF-anisole blends from a detailed kinetic mechanism. Thereafter, numerical simulations were performed for the fuel surrogates using the skeletal mechanisms and a virtual cooperative fuel research (CFR) engine model, under a representative boosted operating condition. In the computational fluid dynamics (CFD) model, the G-equation approach was employed to track the turbulent flame front and the well-stirred reactor model combined with multi-zone binning strategy was used to capture auto-ignition in the end-gas. In addition, laminar flame speed was tabulated for each blend as a function of pressure, temperature and equivalence ratio a priori, and the lookup tables were used to prescribe laminar flame speed as an input to the G-equation model. Parametric spark timing sweeps were performed for each fuel blend to determine the corresponding knock-limited spark advance (KLSA) and 50% burn point (CA50) at the respective KLSA timing. It was observed that despite same RON, MON and engine operating conditions, the TPRF-Anisole blend exhibited markedly different knock-limited performance from the other three blends. This deviation from the octane index (DI) expectation was shown to be caused by differences in laminar flame speed (LFS). However; it was found that relatively large fuel-specific differences in LFS (> 20%) would have to be present to cause any appreciable deviation from the 01 framework. Otherwise, RON and MON would still be robust enough to predict a fuel's knock-limited performance.
Pal, Pinaki↗