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At least 1,711 records · Page 95

Advanced Compressors for CO2-Based Power Cycles and Energy

Pumped thermal energy storage (PTES) is a cost-effective method for grid-scale, long-duration electrical energy storage (LDES). PTES uses a heat pump cycle to transfer thermal energy from a low temperature reservoir (LTR) to a high temperature reservoir (HTR), later using a heat engine cycle to reverse the process. A key component of the PTES system, the heat pump compressor, represents a significant driver to the cost, performance and operating characteristics of the PTES system. For grid-scale charging (>100 MW), traditional compressor scaling charts indicate that the operating conditions needed would be best served by a multistage axial compressor. While frame gas turbine compressors at these power ratings exist and operate at higher pressure ratios than needed for the CO2 PTES system, the inlet pressure and fluid density of this application exceed experience values. A conceptual design of a large-scale CO2 axial compressor was completed, including mean-line estimates of the compressor performance at full power conditions. The results of the conceptual design were used to refine the PTES cycle design, and updated operating conditions provided for further aero design optimization. A roughly one third scale of the first three stages of the 100 MW compressor was designed, built, and tested at relevant PTES charging conditions. Results of this test program are compared against high-resolution computational fluid dynamics models.

Compressor Heat↗

Genetic Algorithm for Hyperparameter Optimization in Gaussian Process Modeling

A genetic algorithm is developed and applied to optimize hyperparameters of convolutional recursively determined dual neural network-Gaussian process (NNGP) kernels. As a specific application of the combined GPNN-GA algorithm, it is applied to image classification in publicly available data of Hyper Suprime-Cam Subaru Strategic Program. Matthews correlation coefficient is calculated based on results of binary star-galaxy classification and used as a fitting function of the GA module of the algorithm. The simulation results confirm significant improvement of the classification accuracy with optimized hyperparameters.

79 ASTRONOMY AND ASTROPHYSICS↗

High-level fuel fabrication facility designs from discrete-event simulation

Like other industrial processes, the production of metallic nuclear fuels (MNF) requires that fabrication facilities be able to reliably meet production demands, operate efficiently, and adhere to federal and local safety regulations. In turn, the set of design variables employed by such a facility, such as operations policies, infrastructure and machinery purchased, and the type and number of staff hired, directly impact a facility’s ability to satisfy these goals. Therefore, facility designers must carefully determine which set of design variable values optimally satisfies these constraints. In this paper, we explore how values for these high-level design variables, namely hiring requirements, can be determined in the context of nuclear fuel manufacturing through the coupling of physics-based and discrete-event simulation technologies. Using the Versatile Test Reactor (VTR) program as a case study, we demonstrate how SCALE and MCNP nuclear physics model outputs can be integrated into ExtendSim discrete-event simulation (DES) models of the fuel fabrication process to determine the optimal number of staff hired to ensure fuel production goals are met, operations comply with effective dose limit regulations, and overall project costs are reduced.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Tough Errors Are no Match (TEAM): Optimizing the quantum compiler for noise resilience

This report summarizes Unitary Fund’s contributions to the Department of Energy’s TEAM project (DE-SC0020266) under Thrust 2: Quantum Programming and Compilation. The central outcomes of this work have been the development of Mitiq, an open-source Python toolkit for applying quantum error mitigation (QEM) techniques to noisy quantum programs, and the invention, benchmarking and theoretical investigation of novel QEM techniques. Additional outcomes include the development of other open source software packages for the usage, simulation and control of quantum computers.

97 MATHEMATICS AND COMPUTING↗

SU-C-209-05: Monte Carlo Model of a Prototype Backscatter X-Ray (BSX) Imager for Projective and Selective Object-Plane Imaging

Purpose: To develop a Monte Carlo N-Particle (MCNP) model for the validation of a prototype backscatter x-ray (BSX) imager, and optimization of BSX technology for medical applications, including selective object-plane imaging. Methods: BSX is an emerging technology that represents an alternative to conventional computed tomography (CT) and projective digital radiography (DR). It employs detectors located on the same side as the incident x-ray source, making use of backscatter and avoiding ring geometry to enclose the imaging object. Current BSX imagers suffer from low spatial resolution. A MCNP model was designed to replicate a BSX prototype used for flaw detection in industrial materials. This prototype consisted of a 1.5mm diameter 60kVp pencil beam surrounded by a ring of four 5.0cm diameter NaI scintillation detectors. The imaging phantom consisted of a 2.9cm thick aluminum plate with five 0.6cm diameter holes drilled halfway. The experimental image was created using a raster scanning motion (in 1.5mm increments). Results: A qualitative comparison between the physical and simulated images showed very good agreement with 1.5mm spatial resolution in plane perpendicular to incident x-ray beam. The MCNP model developed the concept of radiography by selective plane detection (RSPD) for BSX, whereby specific object planes can be imaged by varying kVp. 10keV increments in mean x-ray energy yielded 4mm thick slice resolution in the phantom. Image resolution in the MCNP model can be further increased by increasing the number of detectors, and decreasing raster step size. Conclusion: MCNP modelling was used to validate a prototype BSX imager and introduce the RSPD concept, allowing for selective object-plane imaging. There was very good visual agreement between the experimental and MCNP imaging. Beyond optimizing system parameters for the existing prototype, new geometries can be investigated for volumetric image acquisition in medical applications. This material is based upon work supported under an Integrated University Program Graduate Fellowship sponsored by the Department of Energy Office of Nuclear Energy.

60 APPLIED LIFE SCIENCES↗

Status of ADRIANO R&D in T1015 Collaboration

The physics program for future High Energy and High Intensity experiments requires an energy resolution of the calorimetric component of detectors at limits of traditional techniques and an excellent particle identification. The novel ADRIANO technology (A Dualreadout Integrally Active Non-segmented Option), currently under development at Fermilab, is showing excellent performance on those respects. Results from detailed Monte Carlo studies on the performance with respect to energy resolution, linear response and transverse containment and a preliminary optimization of the layout are presented. A baseline configuration is chosen with an estimated energy resolution of σ(E)/E ≈ 30%/√E , to support an extensive R&D program recently started by T1015 Collaboration at Fermilab. Furthermore, preliminary results from several test beams at the Fermilab Test Beam Facility (FTBF) of a ~ 1λI prototype are presented. Future prospects with ultra-heavy glass are, also, summarized.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

An Early Quantum Computing Proposal

The D-Wave 2X is the third generation of quantum processing created by D-Wave. NASA (with Google and USRA) and Lockheed Martin (with USC), both own D-Wave systems. Los Alamos National Laboratory (LANL) purchased a D-Wave 2X in November 2015. The D-Wave 2X processor contains (nominally) 1152 quantum bits (or qubits) and is designed to specifically perform quantum annealing, which is a well-known method for finding a global minimum of an optimization problem. This methodology is based on direct execution of a quantum evolution in experimental quantum hardware. While this can be a powerful method for solving particular kinds of problems, it also means that the D-Wave 2X processor is not a general computing processor and cannot be programmed to perform a wide variety of tasks. It is a highly specialized processor, well beyond what NNSA currently thinks of as an “advanced architecture.”A D-Wave is best described as a quantum optimizer. That is, it uses quantum superposition to find the lowest energy state of a system by repeated doses of power and settling stages. The D-Wave produces multiple solutions to any suitably formulated problem, one of which is the lowest energy state solution (global minimum). Mapping problems onto the D-Wave requires defining an objective function to be minimized and then encoding that function in the Hamiltonian of the D-Wave system. The quantum annealing method is then used to find the lowest energy configuration of the Hamiltonian using the current D-Wave Two, two-level, quantum processor. This is not always an easy thing to do, and the D-Wave Two has significant limitations that restrict problem sizes that can be run and algorithmic choices that can be made. Furthermore, as more people are exploring this technology, it has become clear that it is very difficult to come up with general approaches to optimization that can both utilize the D-Wave and that can do better than highly developed algorithms on conventional computers for specific applications. These are all fundamental challenges that must be overcome for the D-Wave, or similar, quantum computing technology to be broadly applicable.

97 MATHEMATICS AND COMPUTING↗

Optimization of Fused Bicyclic Allosteric SHP2 Inhibitors

SHP2 is a nonreceptor protein tyrosine phosphatase within the mitogen-activated protein kinase (MAPK) pathway controlling cell growth, differentiation, and oncogenic transformation. SHP2 also participates in the programed cell death pathway (PD-1/PD-L1) governing immune surveillance. Small-molecule inhibition of SHP2 has been widely investigated, including in our previous reports describing SHP099 (2), which binds to a tunnel-like allosteric binding site. To broaden our approach to allosteric inhibition of SHP2, we conducted additional hit finding, evaluation, and structure-based scaffold morphing. These studies, reported here in the first of two papers, led to the identification of multiple 5,6-fused bicyclic scaffolds that bind to the same allosteric tunnel as 2. We demonstrate the structural diversity permitted by the tunnel pharmacophore and culminated in the identification of pyrazolopyrimidinones (e.g., SHP389, 1) that modulate MAPK signaling in vivo. These studies also served as the basis for further scaffold morphing and optimization, detailed in the following manuscript.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Solving the duck curve in a smart grid environment using a non-cooperative game theory and dynamic pricing profiles

With the intermittency that comes with electricity generation from renewables, utilizing dynamic pricing will encourage the demand-side to respond in a smart way that would minimize the electricity costs and flatten the net electricity demand curve. Determining the optimal dynamic pricing profile that would leverage distributed storage to flatten the curve is a novel idea that needs to be studied. Moreover, the economic feasibility of utilizing distributed electrical energy storage is still not given in the literature. Therefore, in this paper, a novel way of solving a citywide dynamic model using a bilevel programming algorithm is introduced. The problem is developed as a novel non-cooperative Stackelberg game that utilizes air-conditioning systems and electrical storage through the end-users to determine the optimal dynamic pricing profile. The results show that the combined effect of utilizing demand-side air-conditioning systems and distributed storage together can flatten the curve while employing the optimal dynamic pricing profile. An economic study is performed to determine the economic feasibility of 20 different cases with different battery designs and the level of solar penetration. Three metrics were used to evaluate the economic performance of each case: the levelized cost of storage, the levelized cost of energy, and the simple payback period. Most cases had levelized cost of storage values lower than 0.457 $/kWh, which is the lower bound available in the literature. Seven out of 16 cases have a simple payback period shorter than the lifetime of the system (25 years). The case with a 100 MW PV power plant and a battery storage of size 597 MWh, was found to be the most promising case with a simple payback period of 12.71 years for the photovoltaic plant and 19.86 years for the demand-side investments.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

In Recognition of Sandia's SCRM Program, Delivering Over 500 Subcontractor Risk Assessments in 2018

The globalization of modern supply chains has resulted in many new risks to Sandia's NW programs and mission. The potential impact of counterfeit products, tampering, theft, malicious software, poor manufacturing and/or development practices, and the influence of foreign governments has become more obvious as new threats and compromises continuously emerge. The Supply Chain Risk Management (SCRM) team was formed specifically to understand and address these risks. We were able to coalesce around these principles to develop and optimize an effective risk assessment process for critical suppliers, called Subcontractor Risk Assessments (SRAs). These elevated screening techniques are planned and delivered in a cost-effective way for Sandia's programs (no increase to purchasing burden rates) and also demonstrate due diligence to DOE/NNSA as a component of Sandia's overall SCRM strategy. SRAs are communicated in a concise 1-page format complete with recommendations as well as links to reference materials for those who require additional details about the SRA process and results.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Robust planning of dynamic wireless charging infrastructure for battery electric buses

Battery electric buses with zero tailpipe emissions have great potential in improving environmental sustainability and livability of urban areas. However, the problems of high cost and limited range associated with on-board batteries have substantially limited the popularity of battery electric buses. The technology of dynamic wireless power transfer (DWPT), which provides bus operators with the ability to charge buses while in motion, may be able to effectively alleviate the drawbacks of electric buses. In this paper, we address the problem of simultaneously selecting the optimal location of the DWPT facilities and designing the optimal battery sizes of electric buses for a DWPT electric bus system. The problem is first constructed as a deterministic model in which the uncertainty of energy consumption and travel time of electric buses is neglected. The methodology of robust optimization (RO) is then adopted to address the uncertainty of energy consumption and travel time. The affinely adjustable robust counterpart (AARC) of the deterministic model is developed, and its equivalent tractable mathematical programming is derived. Both the deterministic model and the robust model are demonstrated with a real-world bus system. The results of our study demonstrate that the proposed deterministic model can effectively determine the allocation of DWPT facilities and the battery sizes of electric buses for a DWPT electric bus system; and the robust model can further provide optimal designs that are robust against the uncertainty of energy consumption and travel time for electric buses.

25 ENERGY STORAGE↗

The allocation of a variable series reactor considering AC constraints and contingencies

The Variable Series Reactors (VSRs) can efficiently control the power flow through the adjustment of the line reactance. When they are appropriately allocated in the power network, the transmission congestion and generation cost can be reduced. Our work proposes a planning model to optimally allocate VSRs considering AC constraints and multi-scenarios including base case and contingencies. The planning model is originally a non-convex large scale mixed integer nonlinear program (MINLP), which is generally intractable. The proposed Benders approach decomposes the MINLP model into a mixed integer linear program (MILP) master problem and a number of nonlinear subproblems. Numerical case studies based on IEEE 118-bus demonstrate the high performance of the proposed approach.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Needs for integrated risk assessment to support optimal environmental management decisions - 15455

Cleaning up legacy waste from 50 years of nuclear weapons production and energy research still remains a challenge for the U.S. Department of Energy (DOE). The DOE environmental management program is currently forecasted to run through at least late 2060's with an estimated liability of $204 billion. Risks to human health of workers and the public, the ecological system, and nuclear safety of cleanup activities continue to drive the cost of DOE's cleanup programs. Currently, these risks are generally assessed and managed independently of each other. Except for DOE self-regulated on-site disposal activities of low-level radioactive waste, risks to human health and the environment are generally under the purview of U.S. Environmental Protection Agency and State regulatory agencies, while nuclear safety risks are regulated by DOE with oversight from the U.S. Nuclear Regulatory Commission and the Defense Nuclear Facilities Safety Board where appropriate. When managing health and environmental risks, the individual regulatory authorities often use an area-by-area (or unit-by-unit), contaminant-by-contaminant (chemical-by-chemical or radionuclide-by-radionuclide) approach, focusing on a single medium (soil, water, or air), a single source (e.g., a burial ground or a processing facility), and a single receptor (e.g, a groundwater well or a creek). This level of segregation in risk evaluations by risk category, geographical location, and operational unit, as well as the corresponding separation of regulatory authorities poses a significant challenge to reaching an optimal decision in prioritizing and managing cleanup activities. This management challenge adds another layer of complexity to large-scale cleanup effort at complex sites such as the Hanford site in eastern Washington. Therefore, to support a scientifically sound, operationally robust decision making process, there is a need for an integrated, holistic approach to risk assessment that addresses the combined effects of all major contributing factors. Previous studies have pointed out the need for integrated risk assessments that address multi-contaminant, multimedia, multi-pathway exposures, for the purposes of evaluating risks to human health and the environment. We believe that a comprehensive risk assessment should also take into nuclear safety risks that are associated with handling of nuclear material either retrieved from burial sites or to be decommissioned from nuclear facilities. Recent efforts, such as the Consortium for Risk Evaluation with Stakeholder Participation (CRESP)-led Hanford site-wide independent risk review that will categorize all types of risks at the Hanford site and the DOE complex-wide risk review mandated by the Fiscal Year 2014 Consolidated Appropriations Act ('Omnibus bill'), are beginning to more comprehensively address this need. This paper provides a categorization of various types of risks present at typical DOE sites, reviews the current risk assessment and management practices, and discusses the needs for integrating nuclear safety into performance and risk assessments for optimal cleanup decisions. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

SPEARS: A Database-Invariant Spectral modeling API

The Spectral Physics Environment for Advanced Remote Sensing (SPEARS) application programming interface (API) is a Python-based, line-by-line, local thermal equilibrium (LTE) spectral modeling code which is optimized for simultaneously synthesizing optical spectra from any combination of fundamental spectroscopic databases. In this article, we contribute two novel spectral modeling techniques to the scientific literature. First we describe how SPEARS integrates a physics-based collisional model for calculating pressure broadening in the absence of available broadening coefficients. With this collisional model implementation, a generalized approach to fundamental spectroscopic databases can be achieved across multiple databases. We also detail our adaptive grid mesh algorithm developed to make the code scalable for simulating large spectral bandwidths at high spectral fidelity using intuitive grid parameters. Here, we present comparisons to other modeling tools, experiments, and provide a discussion on the SPEARS user interface.

47 OTHER INSTRUMENTATION↗

Harnessing Peptide Binding to Capture and Reclaim Phosphate

With rising consumer demands, society is tapping into wastewater as an innovative source to recycle depleting resources. Novel reclamation technologies have been recently explored for this purpose, including several that optimize natural biological processes for targeted reclamation. However, this emerging field has a noticeable dearth of synthetic material technologies that are programmed to capture, release, and recycle specified targets; and of the novel materials that do exist, synthetic platforms incorporating biologically inspired mechanisms are rare. We present here a prototype of a materials platform utilizing peptide amphiphiles that has been molecularly engineered to sequester, release, and reclaim phosphate through a stimuli-responsive pH trigger, exploiting a protein-inspired binding mechanism that is incorporated directly into the self-assembled material network. This material is able to harvest and controllably release phosphate for multiple cycles of reuse, and it is selective over nitrate and nitrite. We have determined by simulations that the binding conformation of the peptide becomes constrained in the dense micelle corona at high pH such that phosphate is expelled when it otherwise would be preferentially bound. However, at neutral pH, this dense structure conversely employs multichain binding to further stabilize phosphate when it would otherwise be unbound, opening opportunities for higher-order conformational binding design to be engineered into this controllably packed corona. With this work, we are pioneering a new platform to be readily altered to capture other valuable targets, presenting a new class of capture and release materials for recycling resources on the nanoscale.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Effect of the mobility on (I-V) characteristics of the MOSFET

MOSFET Transistor was the subject of many studies and research works (electronics, data-processing, telecommunications...) in order to exploit its interesting and promising characteristics. The aim of this contribution is devoted to the effect of the mobility on the static characteristics I-V of the MOSFET. The study enables us to calculate the drain current as function of bias in both linear and saturated modes; this effect is evaluated using a numerical simulation program. The influence of mobility was studied. Obtained results allow us to determine the mobility law in the MOSFET which gives optimal (I-V) characteristics of the component.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Development of a 300 MWe Utility Scale Oxy-Fuel sCO2 Turbine

A 300 MWe direct-fired supercritical carbon dioxide (sCO2) oxy-fuel turbine is being developed that will burn natural gas-fired, coal syngas and even hydrogen mixtures capable of 1,150ºC turbine inlet temperature at 300 bar. This design will significantly improve the state-of-the-art for thermal efficiency and results in a high-pressure stream of CO2 with 98%+ carbon capture, making the power plant near emission-free and more efficient than Natural Gas Combined Cycle (NGCC) plants with carbon capture. This power plant will be capable of burning coal through gasification and cleanup of the synthesis gas (syngas). sCO2 power cycles are a transformational technology for the energy industry, providing higher efficiency heat source energy conversion for conventional and alternative energy sources. This novel cycle significantly reduces capital costs because of smaller equipment footprints, design modularity, and allows for rapid cyclic load and source following to balance solar and wind energy power swings. Oxy-fuel sCO2 cycles take these advantages even further, utilizing higher firing temperatures, improved efficiency, and simpler carbon capture strategies. This turbine will require cooled turbine nozzles and blades as well as advanced thermal management systems to accommodate these high temperatures. The cooled blade heat transfer correlations required new test programs at higher Reynolds number than air-breathing gas turbines for impingement, serpentine, and pin-fin regions. Novel blade optimization was performed to maximize aerodynamic efficiency, while minimizing cooling flows. A turbine layout was generated utilizing individual combustor cans with cooled liners feeding into a 6-stage axial flow turbine with cooled stator nozzles and turbine blades. The case design and thermal management preliminary design will be described.

Moore, Jeffrey↗

SU-E-T-151: Breathing Synchronized Delivery (BSD) Planning for RapicArc Treatment

Purpose: To propose a workflow for breathing synchronized delivery (BSD) planning for RapicArc treatment. Methods: The workflow includes three stages: screening/simulation, planning, and delivery. In the screening/simulation stage, a 4D CT with the corresponding breathing pattern is acquired for each of the selected patients, who are able to follow their own breathing pattern. In the planning stage, one breathing phase is chosen as the reference, and contours are delineated on the reference image. Deformation maps to other phases are performed along with contour propagation. Based on the control points of the initial 3D plan for the reference phase and the respiration trace, the correlation with respiration phases, the leaf sequence and gantry angles is determined. The beamlet matrices are calculated with the corresponding breathing phase and deformed to the reference phase. Using the 4D dose evaluation tool and the original 3D plan DVHs criteria, the leaf sequence is further optimized to meet the planning objectives and the machine constraints. In the delivery stage, the patients are instructed to follow the programmed breathing patterns of their own, and all other parts are the same as the conventional Rapid-Arc delivery. Results: Our plan analysis is based on comparison of the 3D plan with a static target (SD), 3D plan with motion delivery (MD), and the BSD plan. Cyclic motion of range 0 cm to 3 cm was simulated for phantoms and lung CT. The gain of the BSD plan over MD is significant and concordant for both simulation and lung 4DCT, indicating the benefits of 4D planning. Conclusion: Our study shows that the BSD plan can approach the SD plan quality. However, such BSD scheme relies on the patient being able to follow the same breathing curve that is used in the planning stage during radiation delivery. Funded by Varian Medical Systems.

60 APPLIED LIFE SCIENCES↗