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DOE OSTI2024

Dynamic data-driven multiscale modeling for predicting the degradation of a 316L stainless steel nuclear cladding material

Here, we have developed a long short-term memory stacked ensemble (LSTM-SE) surrogate modeling approach that can provide rapid predictions of microstructural evolution and the resultant mechanical properties of American Iron and Steel Institute (AISI) 316L series stainless steel (316LSS) fuel cladding under conditions of varying temperature and radiation dose rate. To acquire training data, we developed and implemented a kinetic Monte Carlo (KMC) model to simulate precipitation kinetics of M 23 C 6 , γ', and G phases within SS316L cladding. Experimentally reported precipitation kinetics of SS316L in literature were linked to the kinetic parameters of the simulated precipitation in our KMC model. The model was then used to simulate microstructure evolution under synthetically generated treatments of varying temperature and radiation dose rate, for periods of up to 3000 hours. Changes in volume fraction, number density, and particle size of precipitates were recorded, and particle area fractions were correlated using statistical methods to develop the surrogate model. Simultaneously, the mechanical properties of the simulated microstructures were evaluated using microstructure-based finite element method (FEM) analysis to determine the elastic modulus, yield stress, ultimate tensile strength, and elongation to failure of the aged microstructures. Using this approach, our surrogate model can predict precipitation behavior within 0.25% volume fraction and mechanical properties within 6% relative error from the values predicted by the KMC and FEM models using 50 training simulations as input. The trained recurrent neural network-based model can return estimations of precipitation kinetics and mechanical properties ~1000 times faster than the physics-based codes. This work demonstrates, as a proof of concept, that reactor material service lifetimes under variable service conditions can be predicted for a statistics-based model from a practicably obtainable dataset.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Dynamic Data-Driven Multiscale Modeling for Predicting Microstructure and Mechanical Properties of 316L Stainless Steel

We have developed a long short-term memory stacked ensemble (LSTM-SE) surrogate modeling approach that can provide rapid predictions of microstructural evolution and the resultant mechanical properties of American Iron and Steel Institute (AISI) 316L series stainless steel (316LSS) fuel cladding under conditions of varying temperature and radiation dose rate. To acquire training data, we developed and implemented a kinetic Monte Carlo (KMC) model to simulate precipitation kinetics of M 23 C 6 , γ', and G phases within SS316L cladding. Experimentally reported precipitation kinetics of SS316L in literature were linked to the kinetic parameters of the simulated precipitation in our KMC model. The model was then used to simulate microstructure evolution under synthetically generated treatments of varying temperature and radiation dose rate, for periods of up to 3000 hours. Changes in volume fraction, number density, and particle size of precipitates were recorded, and particle area fractions were correlated using statistical methods to develop the surrogate model. Simultaneously, the mechanical properties of the simulated microstructures were evaluated using microstructure-based finite element method (FEM) analysis to determine the elastic modulus, yield stress, ultimate tensile strength, and elongation to failure of the aged microstructures. Using this approach, our surrogate model can predict precipitation behavior within 0.25% volume fraction and mechanical properties within 6% relative error from the values predicted by the KMC and FEM models using 50 training simulations as input. The trained recurrent neural network-based model can return estimations of precipitation kinetics and mechanical properties ~1000 times faster than the physics-based codes. This work demonstrates, as a proof of concept, that reactor material service lifetimes under variable service conditions can be predicted for a statistics-based model from a practicably obtainable dataset.

36 MATERIALS SCIENCE↗

DOE OSTI2019

Theoretical and computational studies on the scattering of radio frequency waves by fluctuations

The practical and economic viability of tokamak fusion reactors depends, in a significant way, on the efficiency of radio frequency (RF) waves to deliver energy and momentum to the plasma in the core of the reactor. Among the various attributes of RF waves is their ability to heat magnetically confined plasmas, induce plasma currents in an effort to achieve steady state, and modify the current profile so as to control plasma instabilities like the neoclassical tearing modes. The RF electromagnetic waves, excited by antenna structures placed near the wall of a tokamak, have to propagate through the turbulent plasma in the scrape-off layer (SOL) along their path to the core plasma. While the propagation and damping of RF waves in the core is reasonably well understood, the same is not true for RF propagation through the SOL. In present day fusion devices, the radial width of the SOL is of the order of a few centimeters. In ITER and in future fusion reactors this width will be of the order of tens of centimeters. Any deleterious effects on RF waves due to plasma turbulence in the SOL has to be properly understood in order to optimize the delivery of RF energy and momentum into the core. This paper is on a multi-pronged approach that is being pursued to quantify the effect of SOL plasma on RF waves. The SOL is composed of coherent filamentary, or blob like, structures and incoherent fluctuations. For coherent structures a full-wave theoretical model has been developed. This model is used to benchmark computational codes that are subsequently used to study general distribution of filaments, thereby extending the range of the theoretical formulation. For incoherent fluctuations, a common approach towards quantifying the effects of turbulence is the Kirchhoff technique. This technique is based on physical optics and the wave fields at any point on a spatially varying surface are approximated to be the same as the fields on a tangent plane at that point. The results from the theoretical analysis are compared with full-wave numerical simulations for incoherent fluctuations. The final part of these studies is to construct the effective permittivity of a turbulent plasma that is a mix of coherent and incoherent fluctuations. Towards this end, the ``effective medium approximation'' is being used to construct the permittivity of the turbulent plasma that will be used in full-wave and physical optics studies of scattering. All these approaches are distinctly different from previous studies on the RF wave propagation through turbulent plasmas. The theory and computations discussed in this paper apply to RF waves in any frequency range and for arbitrary variations in density, and reveal new and important physical insights into the scattering of RF waves.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2017

PIC simulations of wave-particle interactions with an initial electron velocity distribution from a kinetic ring current model

Whistler wave-particle interactions play an important role in the Earth inner magnetospheric dynamics and have been the subject of numerous investigations. By running a global kinetic ring current model (RAM-SCB) in a storm event occurred on Oct 23–24 2002, we obtain the ring current electron distribution at a selected location at MLT of 9 and L of 6 where the electron distribution is composed of a warm population in the form of a partial ring in the velocity space (with energy around 15 keV) in addition to a cool population with a Maxwellian-like distribution. The warm population is likely from the injected plasma sheet electrons during substorm injections that supply fresh source to the inner magnetosphere. These electron distributions are then used as input in an implicit particle-in-cell code (iPIC3D) to study whistler-wave generation and the subsequent wave-particle interactions. Here, we find that whistler waves are excited and propagate in the quasi-parallel direction along the background magnetic field. Several different wave modes are instantaneously generated with different growth rates and frequencies. The wave mode at the maximum growth rate has a frequency around 0.62ω ce , which corresponds to a parallel resonant energy of 2.5 keV. Linear theory analysis of wave growth is in excellent agreement with the simulation results. These waves grow initially due to the injected warm electrons and are later damped due to cyclotron absorption by electrons whose energy is close to the resonant energy and can effectively attenuate waves. The warm electron population overall experiences net energy loss and anisotropy drop while moving along the diffusion surfaces towards regions of lower phase space density, while the cool electron population undergoes heating when the waves grow, suggesting the cross-population interactions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2020

Well-to-Wheels Analysis of Zero-Emission Plug-In Battery Electric Vehicle Technology for Medium- and Heavy-Duty Trucks

Conventional diesel medium- and heavy-duty vehicles (MHDVs) create large amount of air emissions. With the advancement in technology and reduction in the cost of batteries, plug-in battery electric vehicles (BEVs) are increasingly attractive options for improving energy efficiency and reducing air emissions of MHDVs. In this paper, we compared the well-to-wheels (WTW) greenhouse gases (GHGs) and criteria air pollutant emissions of MHD BEVs with their conventional diesel counterparts across weight classes and vocations. We expanded the Greenhouse gases, Regulated Emissions, and Energy use in Technologies (GREET) model to conduct the WTW analysis of MHDVs. The fuel economy for a wide range of MHDV weight classes and vocations, over various driving cycles, was evaluated using a high-fidelity vehicle dynamic simulation software (Autonomie). The environmental impacts of MHD BEVs are sensitive to the source of electricity used to recharge their batteries. The WTW results show that MHD BEVs significantly improve environmental sustainability of MHDVs by providing deep reductions in WTW GHGs, nitrogen oxides, volatile organic compounds, and carbon monoxide emissions, compared to conventional diesel counterparts. Increasing shares of renewable and natural gas technologies in future national and regional electricity generation are expected to reduce WTW particulate matters and sulfur oxide emissions for further improvement of the environmental performance of MHD BEVs.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2022

Passive spiral galaxies deeply captured by Subaru Hyper Suprime-Cam

Abstract This paper presents a thousand passive spiral galaxy samples at z = 0.01–0.3 based on a combined analysis of the Third Public Data Release of the Hyper Suprime-Cam Subaru Strategic Program (HSC-SSP PDR3) and the GALEX–SDSS–WISE Legacy Catalog (GSWLC-2). Among 54871 gri galaxy cutouts taken from the HSC-SSP PDR3 over 1072 deg2, we conducted a search with deep-learning morphological classification for candidates of passive spirals below the star-forming main sequence derived by ultraviolet to mid-infrared spectral energy distribution fitting in the GSWLC-2. We then classified the candidates into 1100 passive spirals and 1141 secondary samples based on visual inspections. Most of the latter cases are considered to be passive ringed S0 or pseudo-ringed galaxies. The remaining secondary samples have ambiguous morphologies, including two peculiar objects with diamond-shaped stellar wings. The selected passive spirals have a similar distribution to the general quiescent galaxies on the EWHδ–Dn4000 diagram and concentration indices. Moreover, we detected an enhanced passive fraction of spiral galaxies in X-ray clusters. Passive spirals in galaxy clusters are preferentially located in the midterm or late infall phase on the phase–space diagram, supporting the ram pressure scenario, which has been widely advocated in previous studies. The source catalog and gri-composite images are available on the HSC-SSP PDR3 website 〈https://hsc.mtk.nao.ac.jp/ssp/data-release/〉. Future updates, including integration with a citizen science project dedicated to the HSC data, will achieve more effective and comprehensive classifications.

Shimakawa, Rhythm (ORCID:0000000344422750)↗

DOE OSTI2024

Ba₁₋ₓSrₓFeO₃₋ᵧ as an Improved Oxygen Carrier for Chemical Looping Air Separation: A Computational and Experimental Study

Chemical looping air separation (CLAS) is a promising method to generate pure carbon-dioxide from fuel combustion with a pure oxygen stream, which is produced through the capture, and targeted release, of oxygen from the atmosphere using a solid oxide carrier. The performance of this process depends on the redox characteristics of the oxide carrier. Using experimental oxygen-temperature-programmed desorption (TPD) and thermogravimetric analysis (TGA), the study shows that Ba₀․₇₅Sr₀․₂₅FeO₃ has improved oxygen storage capacity (OSC), oxidation, and reduction kinetics over pristine SrFeO₃ at temperatures ranging from 300-500 °C. The redox energetics computed by using first-principles density functional theory (DFT) calculations also depict the measured trend establishing it as an important descriptor of the measured performance. The Ba₁₋ₓSrₓFeO₃₋ᵧ depicts a Sr-substitution and oxygen stoichiometry induced structural phase transition from hexagonal at low temperatures to pseudo-cubic phase with higher OSC up to T=400 °C. Also, the mechanism leading to this structural phase transition is identified by performing electronic and vibrational structural calculations. This presentation was given on March 8, 2024 at the APS March Meeting in Minneapolis, MN.

Acharya, Shree Ram↗

DOE OSTI2011

INTRACLUSTER MEDIUM OF THE MERGING CLUSTER A3395

We present a detailed imaging and spectral analysis of the merging environment of the bimodal cluster A3395 using X-ray and radio observations. X-ray images of the cluster show five main constituents of diffuse emission: A3395 NE, A3395 SW, A3395 NW, A3395 W, and a filament connecting NE to W. X-ray surface brightness profiles of the cluster did not show any shock fronts in the cluster. Temperature and entropy maps show high-temperature and high-entropy regions in the W, the NW, the filament, and between the NE and SW subclusters. The NE, SW, and W components have X-ray bolometric luminosities similar to those of rich clusters of galaxies but have relatively higher temperatures. Similarly, the NW component has X-ray bolometric luminosity similar to that of isolated groups but with much higher temperature. It is, therefore, possible that all the components of the cluster have been heated by the ongoing mergers. The NE subcluster is the most massive and luminous constituent and other subclusters are found to be gravitationally bound to it. The W component is most probably either a clump of gas stripped off the SW due to ram pressure or a separate subcluster that has merged or is merging with the SW. No X-ray cavities are seen associated with the wide-angle-tailed (WAT) radio source near the center of the SW subcluster. Minimum energy pressure in the radio emission peaks of the WAT galaxy is comparable with the external thermal pressure. The radio spectrum of the WAT suggests a spectral age of {approx}10 Myr.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2025

Revealing the potential of nickel zinc ferrite: Facile synthesis and cost-effective anode for lithium-ion batteries

The increasing demand for lithium-ion batteries (LIBs) underscores the need for cost-effective alternative anode materials to ensure efficient Li-ion storage, given their pivotal role in various industries. This research focuses on the facile synthesis of nickel zinc ferrite (NZFO: Ni 0.65 Zn 0.35 Fe 2 O 4 ) and conducts comprehensive electrochemical analyses to evaluate its potential as a high-capacity alternative anode material for LIBs. The NZFO-CMR [sodium carboxymethyl cellulose (2%) and styrene-butadiene rubber (1%)] exhibited an initial delithiated capacity of ∼1232 mA h g −1 and maintained a stable capacity of around 358 mA h g −1 , along with an average Coulombic efficiency of 99.6% over 200 cycles. Cyclic voltammetry analysis revealed that Li-ion insertion was predominantly governed by ion diffusion, and the consistent correlation observed in electrochemical impedance spectroscopy spectra indicated stable electrochemical behavior throughout cycling. The facile synthesis approach and reasonable electrochemical performance of NZFO suggest its potential as an alternative anode material for advancing LIB's technology.

25 ENERGY STORAGE↗

DOE OSTI2014

Intake of high-fat diet stimulates the risk of ultraviolet radiation-induced skin tumors and malignant progression of papillomas to carcinoma in SKH-1 hairless mice

Previously, we showed that administration of a high-fat diet (HF-diet) to C57BL/6 mice exacerbates their response to short-term UVB radiation-induced inflammation in the skin. To explore the effects of an HF-diet on UVB-induced tumorigenesis, we have used the SKH-1 hairless mouse model in which the mice are exposed to UVB radiation (180 mJ/cm{sup 2}) three times a week for 24 weeks. The development of UVB-induced skin tumors was rapid and the tumor multiplicity and tumor size were significantly higher (P < 0.01–0.005) in the mice fed an HF-diet than the mice fed a control-diet (C-diet). Moreover, the malignant progression of UVB-induced papillomas to carcinomas was higher in HF-diet-fed mice. On analysis of tumors and tumor-uninvolved skin samples from the tumor-bearing mice, we found that administration of an HF-diet significantly enhanced the levels of UVB-induced expression of cyclooxygenase-2 (COX-2), prostaglandin E{sub 2} (P < 0.01), and PGE{sub 2} receptors, and activation of NF-κB in the UVB-exposed skin as well as in tumors. In addition the HF-diet enhanced the expression of proinflammatory cytokines, including tumor necrosis factor-α (P < 0.01), interleukin (IL)-1β (P < 0.01) and IL-6 (P < 0.05) in the UVB-exposed skin as well as in tumors. Western blot analysis revealed that HF-diet enhanced the levels of epidermal cell proliferation, phosphatidylinositol 3-kinase and phosphorylation of Akt at Ser{sup 473} in UVB-exposed skin and skin tumors. Collectively, these data demonstrate that the regular consumption of an HF-diet increases the risk of photocarcinogenesis in mice and that this is associated with enhanced expression of inflammatory mediators in the UVB-exposed skin and tumors. - Highlights: • Consumption of high-fat diet increases UVB-induced skin tumor development in mice. • Intake of high-fat diet stimulates progression of UV-induced papilloma to carcinoma. • Intake of high-fat diet enhances inflammation in UV-exposed skin • Regular consumption of low-fat diet may inhibit the risk of photocarcinogenesis.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2025

Impact of Regional and Seasonal Characteristics on Battery Electric Vehicle Operational Costs in the U.S.

This study investigates the operational cost competitiveness of battery electric vehicles (BEVs) in the United States, considering regional climates, energy prices, and driving patterns. By comparing BEVs with plug-in hybrid electric vehicles (PHEVs), hybrid electric vehicles (HEVs), and the alternative use of BEVs and conventional vehicles (Convs), the analysis incorporates thermal dynamometer tests, real-world vehicle miles traveled (VMT), and state-specific energy prices. Using detailed simulations, the study evaluates energy consumption across varying temperatures and driving distances. The findings reveal that, while BEVs remain cost-effective for short trips in moderate climates, PHEVs are more economical for long-range trips and cold environments, due to the excessive cost of using external direct current fast chargers (DCFCs) and reduced BEV efficiency at low temperatures. HEVs are identified as the most cost-efficient option in regions like New England, characterized by high residential electricity prices. These insights are critical for shaping vehicle electrification strategies, particularly under diverse regional and seasonal conditions, and for advancing policies on alternative energy and fuels.

Kim, Kyung-Ho (ORCID:0009000450851732)↗

DOE OSTI2017

GASP. II. A MUSE View of Extreme Ram-Pressure Stripping along the Line of Sight: Kinematics of the Jellyfish Galaxy JO201

This paper presents a spatially resolved kinematic study of the jellyfish galaxy JO201, one of the most spectacular cases of ram-pressure stripping (RPS) in the GAs Stripping Phenomena in galaxies with MUSE (GASP) survey. By studying the environment of JO201, we find that it is moving through the dense intracluster medium of Abell 85 at supersonic speeds along our line of sight, and that it is likely accompanied by a small group of galaxies. Given the density of the intracluster medium and the galaxy’s mass, projected position, and velocity within the cluster, we estimate that JO201 must so far have lost ∼50% of its gas during infall via RPS. The MUSE data indeed reveal a smooth stellar disk accompanied by large projected tails of ionized (Hα) gas, composed of kinematically cold (velocity dispersion <40 km s{sup −1}) star-forming knots and very warm (>100 km s{sup −1}) diffuse emission, that extend out to at least ∼50 kpc from the galaxy center. The ionized Hα-emitting gas in the disk rotates with the stars out to ∼6 kpc; but, in the disk outskirts, it becomes increasingly redshifted with respect to the (undisturbed) stellar disk. The observed disturbances are consistent with the presence of gas trailing behind the stellar component resulting from intense face-on RPS along the line of sight. Our kinematic analysis is consistent with the estimated fraction of lost gas and reveals that stripping of the disk happens outside-in, causing shock heating and gas compression in the stripped tails.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2015

Enhanced DEA model with undesirable output and interval data for rice growing farmers performance assessment

Agricultural production process typically produces two types of outputs which are economic desirable as well as environmentally undesirable outputs (such as greenhouse gas emission, nitrate leaching, effects to human and organisms and water pollution). In efficiency analysis, this undesirable outputs cannot be ignored and need to be included in order to obtain the actual estimation of firms efficiency. Additionally, climatic factors as well as data uncertainty can significantly affect the efficiency analysis. There are a number of approaches that has been proposed in DEA literature to account for undesirable outputs. Many researchers has pointed that directional distance function (DDF) approach is the best as it allows for simultaneous increase in desirable outputs and reduction of undesirable outputs. Additionally, it has been found that interval data approach is the most suitable to account for data uncertainty as it is much simpler to model and need less information regarding its distribution and membership function. In this paper, an enhanced DEA model based on DDF approach that considers undesirable outputs as well as climatic factors and interval data is proposed. This model will be used to determine the efficiency of rice farmers who produces undesirable outputs and operates under uncertainty. It is hoped that the proposed model will provide a better estimate of rice farmers’ efficiency.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2015

IBEX: An open infrastructure software platform to facilitate collaborative work in radiomics

Purpose: Radiomics, which is the high-throughput extraction and analysis of quantitative image features, has been shown to have considerable potential to quantify the tumor phenotype. However, at present, a lack of software infrastructure has impeded the development of radiomics and its applications. Therefore, the authors developed the imaging biomarker explorer (IBEX), an open infrastructure software platform that flexibly supports common radiomics workflow tasks such as multimodality image data import and review, development of feature extraction algorithms, model validation, and consistent data sharing among multiple institutions. Methods: The IBEX software package was developed using the MATLAB and C/C++ programming languages. The software architecture deploys the modern model-view-controller, unit testing, and function handle programming concepts to isolate each quantitative imaging analysis task, to validate if their relevant data and algorithms are fit for use, and to plug in new modules. On one hand, IBEX is self-contained and ready to use: it has implemented common data importers, common image filters, and common feature extraction algorithms. On the other hand, IBEX provides an integrated development environment on top of MATLAB and C/C++, so users are not limited to its built-in functions. In the IBEX developer studio, users can plug in, debug, and test new algorithms, extending IBEX’s functionality. IBEX also supports quality assurance for data and feature algorithms: image data, regions of interest, and feature algorithm-related data can be reviewed, validated, and/or modified. More importantly, two key elements in collaborative workflows, the consistency of data sharing and the reproducibility of calculation result, are embedded in the IBEX workflow: image data, feature algorithms, and model validation including newly developed ones from different users can be easily and consistently shared so that results can be more easily reproduced between institutions. Results: Researchers with a variety of technical skill levels, including radiation oncologists, physicists, and computer scientists, have found the IBEX software to be intuitive, powerful, and easy to use. IBEX can be run at any computer with the windows operating system and 1GB RAM. The authors fully validated the implementation of all importers, preprocessing algorithms, and feature extraction algorithms. Windows version 1.0 beta of stand-alone IBEX and IBEX’s source code can be downloaded. Conclusions: The authors successfully implemented IBEX, an open infrastructure software platform that streamlines common radiomics workflow tasks. Its transparency, flexibility, and portability can greatly accelerate the pace of radiomics research and pave the way toward successful clinical translation.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2022

Failure Mode and Effects Analysis for a Photovoltaic Inverter

While PV panel reliability continues to increase, PV inverters become the limiting factor for PV system reliability. Consequently, it is critical to have a generic tool from a third party for PV inverter reliability assessment to help 1) utilities/PV farm operators schedule maintenance in advance, and 2) inverter developers improve the next-generation design. However, these two things cannot be accomplished without first understanding the reasons behind inverter failure. Following this idea, as the first step, it is essential to identify and investigate the most failure-prone components within a PV inverter system. After all, any system is only as reliable as the components that are contained within it. This motivates the failure mode and effects analysis (FMEA) work presented for this workshop. The FMEA is conducted as follows: first, the overview of the methodology on the development of the FMEA is presented; then, based on a top-down approach starting from the PV inverter system, critical inverter components with high failure rates are identified and summarized; afterward, a thorough FMEA study at a component-level is performed and its results, including failure modes, failure mechanisms, and critical stressors, are tabulated; finally, according to three rankings (chance of occurrence, severity of occurrence, and ease of detection prior to failure) for each failure mechanism provided by the FMEA, risk priority numbers are calculated and the failure mechanisms along with the critical stressors are ranked in terms of their potentially detrimental effect on the PV inverter.

Brown, Buck↗

DOE OSTI2022

Availability and redundancy design considerations for Electron-Ion Collider cooling water systems and components

The Electron-Ion Collider (EIC) is composed of several large-scale systems, which all require highly available cooling systems based on the Conceptual Design Report. Since the overall EIC availability goal is 85%, all the subsystems will contribute. Availability is defined by the time that a component or system is functional given a required or scheduled run time. The focus of the project was to determine if redundant or extra cooling water and deionized water pumps were needed in a subsystem to increase the overall EIC availability. The largest subsystem in the ring is the 10 o’clock cooling system, so this was used for redundancy analysis. Relationships between the components were defined as parallel, series, or m-out-of-n for the cooling towers, valves, pumps and heat exchangers to perform calculations. A comparison between an original system versus a redundant one was then done using component availability from industry standards. Cost analysis was also performed to see how much the availability and cost would decrease if the redundancy application was not chosen. The Collider-Accelerator Department (CAD) also has a calculation in place for the Relativistic-Heavy Ion Collider (RHIC), so cooling water failure data was collected from their operational log and analyzed for real-life component availability. A comparison of component availability from the CAD data to the industry standards was made through the 10 o’clock cooling system layout. The results showed that the subsystems need to have over a 98% availability for an 85% goal, and that the CAD data is very close to the industry component standards. The cost differential is miniscule compared to the potential availability increase. Therefore, redundant systems can increase the overall EIC availability by a sizable amount and are worth implementing.

43 PARTICLE ACCELERATORS↗

DOE OSTI2019

Astro2020 Science White Paper: Cosmological Synergies Enabled by Joint Analysis of Multi-probe data from WFIRST, Euclid, and LSST

NASA, NSF, and DOE will collectively spend well over $4B this decade and the next on missions and surveys that have dark energy cosmology as one of their primary drivers. WFIRST, Euclid, and LSST are all missions designed to perform dedicated surveys that offer unprecedented statistical constraining power and control of systematic uncertainties. However, there is a growing realization that these missions will be significantly more powerful when the data are processed and analyzed in unison. This will require coordinated cross-survey and interagency effort. With proper attention to how data are jointly processed and analyzed, the combination of these missions will provide constraints and systematics control that is better than the sum of their individual parts, as stated in the title of Jain, et al. (2015). We advocate for the three relevant US agencies to work together with our international partners to ensure that the synergy from these multi-probe missions is fully realized.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2023

A Simplified Method to Evaluate Energy Life Cycle Cost Effectiveness for Electron Ion Collider Infrastructure Design

The new DOE Order 436.1A approved on April 25 th provides instructions to incorporate principles of sustainability early in the project planning and design process. Integral to the principles of sustainability is life cycle cost effectiveness Life Cycle Cost (LCC) Analysis is vital to the sustainable energy efficient design and construction of the Electron Ion Collider (EIC). Reducing energy consumption has a direct impact on reducing life cycle operating costs with benefits to the environment. The early stages of the project are the most influential where design decisions and so life-cycle considerations during this stage can result in significant impacts to the energy footprint of the design. For example, when comparing between various options, it is necessary to compare the energy savings in $\frac{US$}{kWh}$ to the capital cost in US$. And although uncertain by nature, it is important to factor in the expected inflation and discount of future spendings to compare with the cost of immediate capital investment. This tech note presents a tool that engineers can readily use to analyze energy operating costs using an incremental life cycle cost method when comparing different design alternative.

43 PARTICLE ACCELERATORS↗