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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Comparative evaluation and selection of heat exchangers using multicriteria decision-making

Here, this study presents a well-structured method for comparing and selecting Heat Exchanger (HE) technologies for Integrated Energy Systems (IES). The decision to select a HE for a particular IES configuration can vary greatly depending not only on engineering requirements but also on customer’s specific demand. In other words, the HE selection for IES requires a multicriteria decision-making approach, taking into account diverse technical, economic, and safety aspects, as well as the relative priorities considered by energy users. This study employs a HE evaluation approach combining multicriteria decision-making techniques widely used in various industries: quality function deployment (QFD) and analytic hierarchy process (AHP) techniques. Of particular interest is the use of the proposed method to select a high-temperature HEs that couples advanced nuclear reactors and industrial processes. To build a practical basis for comparing HEs within the proposed framework, efforts were made to identify the various HEs requirements for IES purposes. In addition, leveraging the insights obtained from the literature review and the market survey of commercial HE suppliers, a knowledge base was built to facilitate the comparison of each requirement across various HE designs. Also, evaluation metrics were identified for HE requirements with robust rational to enhance the quality of decisions made throughout the proposed evaluation process. The evaluation procedure and knowledge base described in this study can provide a useful basis for those interested in screening the appropriate HE designs for various IES scenarios.

Analytic Hierarchy Process (AHP)↗
DOE OSTI2019

Meta-analysis of 18F-FDG PET/CT in the diagnosis of infective endocarditis

Background: The current diagnosis of infective endocarditis (IE) is based on the modified Duke criteria, which has approximately 80% sensitivity for the diagnosis of native valve endocarditis (NVE), with lower sensitivity for the diagnosis of prosthetic valve endocarditis (PVE) and culture-negative endocarditis. There is preliminary evidence that {sup 18}F-FDG PET/CT is an adjunctive diagnostic test with high accuracy reported in small studies to date. We therefore performed a meta-analysis of studies evaluating the use of PET/CT in the diagnosis of IE to establish a more precise estimate of accuracy. Methods: PubMed, Embase, Cochrane library, CINAHL, Web of Knowledge, and www.clinicaltrials.gov were searched from January 1990 to April 2017 for studies evaluating the accuracy of PET/CT for the evaluation of possible IE. Results: We identified 13 studies involving 537 patients that were included in the meta-analysis. The pooled sensitivity of PET/CT for diagnosis of IE was 76.8% (95% CI 71.8–81.4%; Q = 39.9, P < 0.01; I{sup 2} = 69.9%) and the pooled specificity was 77.9% (95% CI 71.9–83.2%; Q = 44.42, P < 0.01; I{sup 2} = 73.0%). Diagnostic accuracy was improved for PVE with sensitivity of 80.5% (95% CI 74.1–86.0%; Q = 25.5, P < 0.01; I{sup 2} = 72.5%) and specificity of 73.1% (95% CI 63.8–81.2%; Q = 32.1, P < 0.01; I{sup 2} = 78.2%). Additional extracardiac foci of infection were found on 17% of patients on whole body PET/CT. Conclusion: PET/CT is a useful adjunctive diagnostic tool in the evaluation of diagnostically challenging cases of IE, particularly in prosthetic valve endocarditis. It also has the potential to detect clinically relevant extracardiac foci of infection, malignancy, and other sources of inflammation leading to more appropriate treatment regimens and surgical intervention.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2022

Multiscale simulation of integrated energy system and electricity market interactions

Accelerating the deep decarbonization of the world's electric grids requires the coordination of complex energy systems and infrastructures across timescales from seconds to decades. Here, we present a new multiscale simulation framework that integrates process- and grid-centric modeling paradigms to better design, operate, and control integrated energy systems (IESs), which combine multiple technologies, in wholesale energy markets. Traditionally, IESs are analyzed with a process-centric paradigm such as levelized cost of electricity (LCOE) or annualized net revenue, ignoring important interactions with electricity markets. This framework explicitly models the complex interactions between an IES's bidding, scheduling, and control decisions and the energy market's clearing and settlement processes, while incorporating operational uncertainties. Through two case studies, we show the importance of understanding and quantifying complex resource-grid interactions. In case study 1, we demonstrate that optimized bidding from one resource shifts the profit distribution for all energy systems in the market. This result suggests new and more flexible IES technologies can disrupt the economics of all market participants, possibly leading to accelerated retirements of less flexible resources. Interestingly, the optimized bidding has little impact on grid-level aggregate statistics, such as total generation costs and renewable penetration rate. While aggregate modeling strategies may remain valid under some IES adoption scenarios for analysis focused on regional outcomes, direct comparisons of IES technologies at specific locations without considering these interactions may lead to misleading or incorrect conclusions. In case study 2, we consider the design and flexible operation of IESs that hybridize conventional generators with energy storage. Through a sensitivity analysis, we find that as the size of the storage system increases, the total number of start-ups for coal- and natural gas-based IESs reduced by 25% and 33.6%, and the total thermal generator ramping (i.e., mileage) reduced by 86.5% and 62.5%, respectively. This shows the primary benefit of storage may not be reduced operational costs (which do not change significantly) but fewer start-ups and less ramping, which may greatly simplify the design, operation, and control of carbon capture systems. The new modeling and optimization capabilities from this work enable the coupling of rigorous, dynamic process models with grid-level production cost models to quantitatively identify the nuanced interdependencies across these vast timescales that must be addressed to realize clean, safe, and secure energy production. Moreover, the proposed general multiscale simulation framework is applicable to all IES technologies and can be easily extended to consider other energy carriers (e.g., hydrogen, ammonia) and energy infrastructures (e.g., natural gas pipelines).

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2017

Water Exchange Rate Constant as a Biomarker of Treatment Efficacy in Patients With Brain Metastases Undergoing Stereotactic Radiosurgery

Purpose: This study was designed to evaluate whether changes in metastatic brain tumors after stereotactic radiosurgery (SRS) can be seen with quantitative MRI early after treatment. Methods and Materials: Using contrast-enhanced MRI, a 3-water-compartment tissue model consisting of intracellular (I), extracellular-extravascular (E), and vascular (V) compartments was used to assess the intra–extracellular water exchange rate constant (k{sub IE}), efflux rate constant (k{sub ep}), and water compartment volume fractions (M{sub 0,I}, M{sub 0,E}, M{sub 0,V}). In this prospective study, 19 patients were MRI-scanned before treatment and 1 week and 1 month after SRS. The change in model parameters between the pretreatment and 1-week posttreatment scans was correlated to the change in tumor volume between pretreatment and 1-month posttreatment scans. Results: At 1 week k{sub IE} differentiated (P<.001) tumors that had partial response from tumors with stable and progressive disease, and a high correlation (R=−0.76, P<.001) was observed between early changes in the k{sub IE} and tumor volume change 1 month after treatment. Other model parameters had lower correlation (M{sub 0,E}) or no correlation (k{sub ep}, M{sub 0,V}). Conclusions: This is the first study that measured k{sub IE} early after SRS, and it found that early changes in k{sub IE} (1 week after treatment) highly correlated with long-term tumor response and could predict the extent of tumor shrinkage at 1 month after SRS.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2019

Probing Reactivity of Gold Atoms with Acetylene and Ethylene with VUV Photoionization Mass Spectrometry and Ab Initio Studies

Reaction of gold atoms with acetylene and ethylene in a laser ablation source produces a number of gold-containing species. Their photoionization efficiency (PIE) curves are measured using tunable vacuum ultraviolet (VUV) radiation at the Advanced Light Source. Their structures are assigned by comparing the experimental ionization energies and PIE curves to those of potential isomers calculated at the CAM-B3LYP/aug-cc-pVTZ level. For smaller molecules, the contribution of ionization to excited electronic states of the cation is also included using photoionization cross sections calculated using ePolyScat . Reaction with acetylene produces adducts Au(C 2 H 2 ) and Au(C 2 H 2 ) 2 , as well as HAu(C 4 H 2 ). Reaction with ethylene leads to adducts Au(C 2 H 4 ), Au(C 2 H 4 ) 2 , an adduct with a gold dimer, Au 2 (C 2 H 4 ), as well as the gold hydrides AuH, HAu(C 2 H 4 ), and HAu(C 4 H 4 ). [Au,C4,H7] is also observed, and it likely corresponds to a gold alkyl, H 2 C$=$C(H)-Au(C 2 H 4 ). Reactions leading to production of odd-hydrogen species are endothermic and are likely due to translationally or electronically excited gold atoms. These measurements provide the first directly measured ionization energy for gold hydride, IE(AuH) = 10.25 ± 0.05 eV. Combining this value with the dissociation energy of AuH + gives a dissociation energy D 0 (AuH) = 3.15 ± 0.12 eV. Several other ionization energies are measured: IE(Au 2 (C 2 H 4 )) = 8.42 ± 0.05 eV, IE(HAu(C 2 H 4 )) = 9.35 ± 0.05 eV, IE(HAu(C 4 H 2 )) = 8.8 ± 0.1 eV, and IE(HAu(C 4 H 4 )) = 8.8 ± 0.1 eV.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Modeling and control of nuclear–renewable integrated energy systems: Dynamic system model for green electricity and hydrogen production

The need for decarbonization and diversification of energy resources has led to the development of integrated energy systems (IESs), where multiple resources supply more than one energy sector. Here, one such IES with small modular nuclear reactors and renewables (wind and solar) as generating resources, catering to the demand of the electric grid while producing hydrogen for industries, is modeled in this paper. The physics-based component models are represented using the Modelica language and interconnected to form the IES. The control and coordination of the overall system are ensured by designing a suitable control architecture composed of individual subsystem-level controls and supervisory control. The dynamic performance and the load-following capability of the IES are evaluated, while satisfying the safe operational limits of the components. Different configurations and modes of IES operation are considered, where the adaptability of the control system in the presence of varying demands and renewable generations is validated. The simulation results indicate that hydrogen as a flexible load facilitates the supply of varying grid demand. Additionally, the renewables are also accommodated into the IES owing to the flexibility of the balance of plant associated with the nuclear reactors.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Review and Modeling of Integrated Energy Systems with Nuclear Reactor Coupled Desalination and District Heating

Detailed reviews of a past advanced nuclear reactor based integrated energy system, as well as other nuclear reactor and fossil fuel based integrated energy systems have been performed for this work. Review of the utilization of heat from nuclear reactors for various applications and cogeneration has been done. The heat can be utilized by extraction of the steam from the turbine while the steam is still at a desired temperature. While use of nuclear process heat for district heating in countries like Finland, France, China, Poland, and elsewhere is discussed, more focus of the review has been given on nuclear desalination processes. Integrated energy systems (IES) where distinct types of reactors like PWR, BWR, sodium cooled fast reactor, heavy water reactor and other advanced reactors are coupled with various nuclear desalination processes like multi-effect distillation (MED), multi-stage flashing (MSF) and reverse osmosis (RO) methods have been discussed. The nuclear desalination plant at Aktau has been discussed in more detail due to its decades of successful operation. The IES of the Aktau plant coupled with 5-effect MED desalination plant has been taken as a reference for modeling the Open Modelica (OM) based IES of this work. Here, the OM IES model shows good agreement with the MED plant output of Aktau and can be extended for future applications of IES.

42 ENGINEERING↗
DOE OSTI2021

Hybrid Simulation Framework

HYBRID is a modeling toolset to assess the economic viability of Nuclear-Renewable Integrated Energy Systems (N-R IES). The frameworks enabling this toolset are INL’s RAVEN, its CashFlow plugin and the Modelica language. The toolset includes sample RAVEN workflows performing economic assessments. These workflows consist of: generation of stochastic time series and application of probabilistic analysis and optimization algorithms (RAVEN); a library of Modelica models representing the physical behavior of N-R IES; and the CashFlow plugin mapping physical performance to economic performance. The toolset allows assembling existing and new models such as nuclear reactors, renewable energy sources, energy storage, gas turbines, industrial processes, etc. into an N-R IES. The toolset workflows evaluate the dynamics of the N-R IES responding to stochastic conditions (electricity demand, price, etc.) and optimize the dispatch economics as well as N-R IES capacity planning.

Epiney, Aaron↗
DOE OSTI2022

Dependencies of Four Mechanisms of Secondary Ice Production on Cloud-Top Temperature in a Continental Convective Storm

Various mechanisms of secondary ice production (SIP) cause multiplication of numbers of ice particle, after the onset of primary ice. A measure of SIP is the ice enhancement ratio (“IE ratio”) defined here as the ratio between number concentrations of total ice (excluding homogeneously nucleated ice) and active ice-nucleating particles (INPs). A convective line observed on 11 May 2011 over the Southern Great Plains in the Mesoscale Continental Convective Cloud Experiment (MC3E) campaign was simulated with the “Aerosol–Cloud” (AC) model. AC is validated against coincident MC3E observations by aircraft, ground-based instruments, and satellite. Four SIP mechanisms are represented in AC: the Hallett–Mossop (HM) process of rime splintering, and fragmentation during ice–ice collisions, raindrop freezing, and sublimation. The vertical profile of the IE ratio, averaged over the entire simulation, is almost uniform (10 2 to 10 3 ) because fragmentation in ice–ice collisions dominates at long time scales, driving the ice concentration toward a theoretical maximum. The IE ratio increases with both the updraft (HM process, fragmentation during raindrop freezing, and ice–ice collisions) and downdraft speed (fragmentation during ice–ice collisions and sublimation). As reported historically in aircraft sampling, IE ratios were predicted to peak near 10 3 for cloud-top temperatures close to the −12°C level, mostly due to the HM process in typically young clouds with their age less than 15 min. Here, at higher altitudes with temperatures of −20° to −30°C, the predicted IE ratios were smaller, ranging from 10 to 10 2 , and mainly resulted from fragmentation in ice–ice collisions.

Aerosols↗
DOE OSTI2018

Crystalline Silicotitanate ion exchange media long-term storage evaluation

Crystalline Silicotitanate a (CST) ion exchange media is produced in an engineered form, known as IONSIV™ IE-911. This material has been tested extensively for use in removing 137 Cs from Savannah River Site (SRS) and Hanford site tank waste. This inorganic material is highly selective for removing cesium ions, even in the presence of high concentrations of sodium and potassium ions and is tolerant of the harsh conditions of the varying tank chemistries. A batch of caustic washed IE-911 that had been produced by the supplier and received at SRS in 2001 was tested to verify that it was still in good condition after the extended storage. This testing involved standard batch contacts to measure the removal of Cs from simulated tank waste. This report describes the results of testing performed to verify that the IE-911 matches the performance of previous batches of this media. To confirm that the performance of IE-911 is similar to previous batches and that no degradation had occurred during storage, batch contact testing was performed using SRNL’s standard methodology using a non-radioactive SRS Average Waste Simulant composition utilized in previous studies. Batch contact kinetics testing was also conducted to determine cesium loading on this batch versus time. The cesium equilibrium loading isotherm in SRS simulant at 23°C was compared to ZAM isotherm model predictions and previous test results with IE-911 media. The measured and predicted distribution coefficients and cesium loading (“Q”) are shown in Table ES-1. The physical properties of the material were also determined, including density, moisture content, and particle size.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2019

Tank Closure Cesium Removal Project CST Simulant Cesium Batch Contact Kinetics Test Results and Column Performance Predictions

To evaluate the cesium removal capabilities of the caustic-washed R9120-B version of crystalline silicotitanate (CST) ion exchange media from Savannah River Site (SRS) waste during Tank Closure Cesium Removal (TCCR) column processing, batch contact kinetics tests were performed at 23 °C in SRS Average simulant. Cesium loading kinetics data was also collected (in current and previous testing; King, et al., 2018a) using the same simulant for an older CST sample (IE- 911) which was caustic-washed by the vendor many years ago and was recently retrieved from drums stored at SRS. (Note that R9120-B and IE-911 are believed to be identical materials, after the R9120-B was caustic washed by SRNL, and differ only by particle size and manufacturing date, and thus can be considered different batches). Although cesium loading kinetics testing can be conducted more rigorously using dynamic column tests, the batch contact method requires less simulant and considerably less experimental effort. Average percent removal data for batch contact samples for the two CST batches are provided in Table ES-1. Faster cesium uptake was observed with IE-911, although the loading rates for the two media batches were similar. After 5.5 hours of CST contact, 81% cesium removal was observed with R9120-B versus 86% removal with IE-911. Although these differences are small, the trend is consistent across the timed results, with the larger bead material always loading slower. These seemingly small differences in percent removal are believed to have a large impact on the column performance. Cesium loading curves for the two CST batches are provided in Figure ES-1 below. Faster cesium loading with IE-911 CST is presumed to be associated with the smaller average particle diameter (408 μm mean volume diameter) versus R9120-B (572 μm diameter). Cesium loading kinetic data was needed to conduct column performance comparisons (i.e., model predictions) for the two CST batches.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

Cesium Removal Performance Comparisons of Crystalline Silicotitanate Media Batches with Savannah River Site Waste Simulant

The Tank Closure Cesium Removal (TCCR) system uses ion exchange columns filled with Crystalline Silicotitanate (CST) media to process radioactive waste solutions for the removal of Cs137. TCCR currently focuses on dissolving Savannah River Site (SRS) Tank 10H waste (primarily sodium salt cake solids) within the tank followed by at-tank ion exchange column treatment. Plans are underway to prepare and install a second TCCR unit at SRS. Capacity and particle size differences exist between archived (IE-911) and more recently-prepared CST media batches (9120- B and 9140-B). Side-by-side comparison testing was performed to evaluate the cesium removal performance of each batch to aid in selecting the preferred CST batch and media characteristics to load into the second TCCR unit. Batch contact equilibrium and flow-through column tests have been conducted with three CST batches using an SRS Average Simulant. Simulant batch contact equilibrium cesium loading results for the three CST batches (including two lots of one batch) are provided in Table ES-1. The 35 °C data indicates that the archived IE-911 batch has a higher cesium capacity than recently-prepared CST media and that the minor TCCR CST 9120-B media lot (2099000035) has similar cesium removal performance to the major TCCR lot (2099000034). Tests conducted at 25 ºC for the archived IE-911 CST batch indicated lower cesium removal performance with this simulant batch than was observed recently with a different SRS Average Simulant batch. A dilution factor (DF) is typically utilized when modeling engineered CST media cesium loading performance to account for mass contributions from the binder material. In cases where CST performance is lower than expected, this factor includes corrections for the binder and for low performance. The ZAM (Zheng, Anthony, and Miller) Isotherm Model DF values are provided in Table ES-1 for each simulant batch contact result. DF values near 0.5 were determined for the 9120-B and 9140-B CST batch contact tests while DF values near 0.6 (20% higher) were determined for the tests with IE-911. These dilution factors are lower than recently observed with a different SRS Average Simulant batch (9140-B DF = 0.68; IE-911 DF = 1.0). Based on these results, it appears that some component in the simulant solution used for equilibrium testing may have resulted in reduced cesium loading on the CST media.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

Data-Informed Evaluation Framework for Integrated Energy Systems: Insights from Power, Process Heat, and Hydrogen Production Applications

The multi-criteria decision analysis (MCDA) framework provides a systematic evaluation of the diverse preferences and performance metrics associated with alternative solutions. This approach is advantageous over a single-criterion methodology, which are only valid under conditions that assume ceteris paribus or an "apples-to-apples" comparison. However, selecting suitable technologies for integrated energy systems (IES) can be likened to an "apples-to-oranges" comparison, given the heterogeneous factors at stake. These factors include economics and performance parameters, geological compatibility, and environmental impacts. Consequently, past research has often employed a mixture of qualitative and quantitative criteria tailored to the specific interests of each study. While the method proves effective in handling the intricate interplay of criteria, the resulting rankings and scores can vary from study to study. This inconsistency is introduced from the use of subjectively defined thresholds and weights. As a result, decision-makers frequently find it challenging to establish clear connections between specific criteria and the resulting scores, as the transformation of criteria into ordinal scores results in a substantial loss of information. To address this challenge, we introduce a data-informed IES evaluation framework that offers comprehensive, interpretable, and traceable evaluations backed by quantifiable rationale. First, we identified key IES evaluation criteria from a decade of literature, focusing on relevant IES applications in power, process heat, and hydrogen production. We leveraged state-of-the-art cost estimates from the Idaho National Laboratory (INL) and technical data from 78 reactor designs from the International Atomic Energy Agency (IAEA) and the Organization for Economic Co-operation and Development - Nuclear Energy Agency (OECD-NEA). Lastly, we established thresholds by analyzing the mean, variance, root mean square, and slope of values across alternatives, categorizing the preferences of decision-makers into distinct utility functions, such as linear, saturating, exponential, and stepwise. Our approach yielded two main outcomes: (1) it provided consistent assessments across different stakeholder groups and (2) it visualized uncertainties in the decision-making context via comprehensive sensitivity analysis. To demonstrate the impact of our framework, we conducted case studies on 6 reactor designs (AP1000, NuScale, BWRX-300, Xe-100, eVinci, iMSR) for the three applications. Our data-driven framework proved to be highly effective in addressing heterogenous uncertainties faced by varied decision-makers? preferences and IES applications, as well as cost and technical estimates of advanced reactors.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Beyond Price-Taker: Multiscale Optimization of a Wind-Battery Integrated Energy System within the Wholesale Electricity Market

This work presents the optimization of a wind-battery IES using the multiscale optimization framework proposed in our previous work to quantify errors from the price-taker assumption. The framework, built over Prescient (an open-source package for solving production cost models), is applied to the RTS-GMLC dataset, an open-source dataset that is representative of the southwest U.S. wholesale electricity market. The framework provides detailed bidding, market clearing, and control processes of an IES, and it can quantify how the IES interacts with the market. In this work, we use the retrofit of a wind farm with a battery storage system as an example to show the difference in the market outcomes and revenues obtained from both price-taker and multiscale optimization approaches. Our work goes beyond price-taker and deep dives into quantifying IES-market interaction in optimizing IES. This framework enables users to explore how different design and operation decisions of energy systems interact with the market and provides a more accurate evaluation than the price-taker assumption.

Chen, Xinhe↗
DOE OSTI2024

Energy Technology Proving Ground Program Plan

New methods of energy production and distribution are required to meet clean energy goals and demands across all U.S. energy sectors. Idaho National Laboratory’s (INL) Integrated Energy Systems (IES) initiative is enabling clean energy research, development, and demonstration (RD&D) activities. To date, IES demonstration programs have been limited by distributed infrastructure and a lack of large-scale facilities to accommodate industry-scale research of Technical Readiness Level (TRL) 6-8 technologies. The IES initiative plans to eliminate these constraints by establishing a new research complex at INL known as the Energy Technology Proving Ground (Proving Ground) to be led by the Energy and Environment Science and Technology Directorate. The Energy and Environment Science and Technology (EES&T) directorate, one of five Idaho National Laboratory (INL) RD&D organizations, focuses on clean energy technologies that anchor the industry-enabling research of the Proving Ground. The Proving Ground will combine diverse clean energy systems into lean integrated test bed of independent multiscale capabilities available to the government and commercial industries to perform research; and will enable INL’s goal of becoming a Net-Zero entity by 2031. This program encompasses existing and new research space at both the in-town Research and Education Campus (REC) and the Arco desert site (the Site). The Proving Ground will support the maturation of IES technologies from TRL 1 through 8 by providing the infrastructure and capabilities needed to sustain a continuum of RD&D from basic science to industry-scale. To establish The Proving Ground and meet INL’s net-zero goals by 2031, nine research program areas have been identified within the IES initiative that require expanded and new capital infrastructure. This program plan provides guidance for establishing the Proving Ground at the Site for plug-and-play pilot testing and proofing of integrated energy system functionality including fission and renewable energy sources for industry driven application platforms.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

Energy Technology Proving Ground FY-2026 Program Plan (Rev.1)

New methods of energy production and distribution are required to meet clean energy goals and demands across all U.S. energy sectors. Idaho National Laboratory’s (INL) Integrated Energy Systems (IES) initiative is enabling clean energy research, development, and demonstration (RD&D) activities. To date, IES demonstration programs have been limited by distributed infrastructure and a lack of large-scale facilities to accommodate industry-scale research of Technical Readiness Level (TRL) 6-8 technologies. The IES initiative plans to eliminate these constraints by establishing a new research complex at INL known as the Energy Technology Proving Ground (Proving Ground) to be led by the Energy and Environment Science and Technology Directorate. The Energy and Environment Science and Technology (EES&T) directorate, one of five Idaho National Laboratory (INL) RD&D organizations, focuses on clean energy technologies that anchor the industry-enabling research of the Proving Ground. The Proving Ground will combine diverse clean energy systems into lean integrated test bed of independent multiscale capabilities available to the government and commercial industries to perform research; and will enable INL’s goal of becoming a Net-Zero entity by 2031. This program encompasses existing and new research space at both the in-town Research and Education Campus (REC) and the Arco desert site (the Site). The Proving Ground will support the maturation of IES technologies from TRL 1 through 8 by providing the infrastructure and capabilities needed to sustain a continuum of RD&D from basic science to industry-scale. To establish The Proving Ground and meet INL’s net-zero goals by 2031, nine research program areas have been identified within the IES initiative that require expanded and new capital infrastructure. This program plan provides guidance for establishing the Proving Ground at the Site for plug-and-play pilot testing and proofing of integrated energy system functionality including fission and renewable energy sources for industry driven application platforms.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
NASA NTRS1998

Industrial Engineering Lifts Off at Kennedy Space Center

When the National Aeronautics and Space Administration (NASA) began the Space Shuttle Program, it did not have an established industrial engineering (IE) capability for several probable reasons. For example, it was easy for some managers to dismiss IE principles as being inapplicable at NASA's John F. Kennedy Space Center (KSC). When NASA was formed by the National Aeronautics and Space Act of 1958, most industrial engineers worked in more traditional factory environments. The primary emphasis early in the shuttle program, and during previous human space flight programs such as Mercury and Apollo, was on technical accomplishments. Industrial engineering is sometimes difficult to explain in NASA's highly technical culture. IE is different in many ways from other engineering disciplines because it is devoted to process management and improvement, rather than product design. Images of clipboards and stopwatches still come to the minds of many people when the term industrial engineering is mentioned. The discipline of IE has only recently begun to gain acceptance and understanding in NASA. From an IE perspective today, the facilities used for flight hardware processing at KSC are NASA's premier factories. The products of these factories are among the most spectacular in the world: safe and successful launches of shuttles and expendable vehicles that carry tremendous payloads into space.

Barth, Tim↗
DOE OSTI2017

Quantification of functional impact classification on the current U.S. nuclear fleet

Currently, nuclear power generates only a small fraction of the world's electricity, though it does have the potential to meet the needs of the world as long as its production can compete with the alternative energy base load producers. In U.S the commercial nuclear fleet comprises of Light Water Reactors (LWRs), consisting of Pressurized Water Reactors (PWRs) and Boiling Water Reactors (BWRs). Many plants experience multiple events each year, which lead to reactor trips or scrams. This subsequently leads to plants being off the grid, which is not an economically favorable situation in the current energy markets. This study helps identify functional impact (FI) event categories for both PWR's and BWR's. Understanding that not all events and their causes can be anticipated, current industry best practices implement lessons learned to provide challenges and issues identification. In turn these are studied to achieve improved operational practices, and design modifications. This leads to overall enhanced resiliency. FI groups are the categories of initiating events (IE). IEs are unplanned events that occur while a nuclear plant is in critical operation, and requires that the plant be shut down to achieve a stable state. When a risk cannot be eliminated, IEs are identified and studied to reduce the risk and contribute to the identification of mitigations, safer designs and operational practices. Breaking IE events into groups' results in the classification of FI groups. A FI group is a risk-significant event category that could impact the ability of a NPP to remove decay heat from the reactor. Inability to remove decay heat from the reactor has the potential to lead to core damage. For an event to be considered a FI, it must be associated with a manual or automatic reactor trip, irrespective of the order of events. In addition, the plant must be at or above the point of adding heat and the event must happen before or shortly after a reactor trip. One or more FIs may be identified in any individual reactor trip sequence. The relationship between FI sequence, and/or frequency per a plant event is outside the scope of this paper. For example, the loss of offsite power (LOOP) can occur from eternal events (i.e. weather, human, wildlife etc.). This results in an event that requires a transfer of power to an emergency source, such as a generator, which produces a reactor trip and then a closure of main steam isolation valves (MSIVS). The FI applicable to this reactor trip sequence would be LOOP and closure of at least one MSIV in each main steam line. The results presented herein are focused on the analysis and evaluation of FI event categories. Only FI categories that can be found in IE studies, Initialing Events Spreadsheet and are recorded in a historical review of Licensee Event Reports (LERs) from 1988 through 2013. The results of this analysis can support plant decisions, design, procedures, and identify weakness.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗