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Development and Characterization of High-Efficiency, High-Specific Impulse Xenon Hall Thrusters

This dissertation presents research aimed at extending the efficient operation of 1600 s specific impulse Hall thruster technology to the 2000 to 3000 s range. Motivated by previous industry efforts and mission studies, the aim of this research was to develop and characterize xenon Hall thrusters capable of both high-specific impulse and high-efficiency operation. During the development phase, the laboratory-model NASA 173M Hall thrusters were designed and their performance and plasma characteristics were evaluated. Experiments with the NASA-173M version 1 (v1) validated the plasma lens magnetic field design. Experiments with the NASA 173M version 2 (v2) showed there was a minimum current density and optimum magnetic field topography at which efficiency monotonically increased with voltage. Comparison of the thrusters showed that efficiency can be optimized for specific impulse by varying the plasma lens. During the characterization phase, additional plasma properties of the NASA 173Mv2 were measured and a performance model was derived. Results from the model and experimental data showed how efficient operation at high-specific impulse was enabled through regulation of the electron current with the magnetic field. The electron Hall parameter was approximately constant with voltage, which confirmed efficient operation can be realized only over a limited range of Hall parameters.

Hofer, Richard R.↗

Alternative Optimizations of X-ray TES Arrays: Soft X-rays, High Count Rates, and Mixed-Pixel Arrays

We are developing arrays of superconducting transition-edge sensors (TES) for imaging spectroscopy telescopes such as the XMS on Constellation-X. While our primary focus has been on arrays that meet the XMS requirements (of which, foremost, is an energy resolution of 2.5 eV at 6 keV and a bandpass from approx. 0.3 keV to 12 keV), we have also investigated other optimizations that might be used to extend the XMS capabilities. In one of these optimizations, improved resolution below 1 keV is achieved by reducing the heat capacity. Such pixels can be based on our XMS-style TES's with the separate absorbers omitted. These pixels can added to an array with broadband response either as a separate array or interspersed, depending on other factors that include telescope design and science requirements. In one version of this approach, we have designed and fabricated a composite array of low-energy and broad-band pixels to provide high spectral resolving power over a broader energy bandpass than could be obtained with a single TES design. The array consists of alternating pixels with and without overhanging absorbers. To explore optimizations for higher count rates, we are also optimizing the design and operating temperature of pixels that are coupled to a solid substrate. We will present the performance of these variations and discuss other optimizations that could be used to enhance the XMS or enable other astrophysics experiments.

Kilbourne, C. A.↗

The Influence of Mineralogy on Recovering Organic Acids from Mars Analogue Materials Using the One-Pot Derivatization Experiment on the Sample Analysis at Mars(SAM) Instrument Suite

The search for complex organic molecules on Mars, including important biomolecules such as amino acids and carboxylic acids, will require a chemical extraction and a derivatization step to transform these organic compounds into species that are sufficiently volatile to be detected by gas chromatography mass spectrometry (GCMS). We have developed a ''one-pot'' extraction and chemical derivatization protocol using N-methyl-N-(tert-butyldimethylsilyl) trifluoroacetamide (MTBSTFA) and dimethylformamide (DMF) for the Sample Analysis at Mars (SAM) experiment instrument suite on NASA's the Mars Science Laboratory (MSL) mission. The temperature and duration of the derivatization reaction, pre-concentration of chemical derivatives, and gas chromatographic separation parameters have been optimized under SAM instrument design constraints. MTBSTFA/DMF extraction and derivatization at 300 1C for several minutes of a variety of terrestrial Mars analog materials facilitated the detection of amino acids and carboxylic acids in a surface soil sample collected from the Atacama Desert and a carbonate-rich stromatolite sample from Svalbard. However, the rapid reaction of MTBSTFA with water in several analog materials that contained high abundances of hydrated minerals, and the possible deactivation of derivatized compounds by iron oxides, as detected by XRD/XRF using the CheMin field unit Terra, proved to be highly problematic for the direct extraction of organics using MTBSTFA. The combination of pyrolysis and two different wet-chemical derivatization methods employed by SAM should enable a wide range of organic compounds to be detected by GCMS if present on Mars.

MSL↗

Modeling Self-Pressurization and Spray Bar Pressure Control of A Cryogenic Storage Tank in Normal Gravity

This paper presents computational fluid dynamics (CFD) models for simulating self-pressurization and spray-bar pressure control processes in a large-scale liquid hydrogen storage tank under normal gravity conditions. For self-pressurization, the model employs the kinetics-based Schrage equation alongside the volume-of-fluid (VOF) method to account for interfacial mass transfer. The CFD predictions of pressure and temperature are compared with experimental data from the Multipurpose Hydrogen Test Bed (MHTB) experiment, and the predicted interfacial mass transfer rates are also presented. A CFD model simulating pressure control using a spray bar has also been developed. An Eulerian-Lagrangian approach models the interactions between discrete droplets and the continuous ullage (vapor) phase. The spray model is coupled with the VOF method by tracking droplets in the ullage and removing them when they reach the liquid interface. The T-sat model calculates droplet-ullage heat and mass transfer, where droplets warm up to the saturation temperature corresponding to the ullage vapor pressure before evaporating while remaining at the saturation temperature. The evolution of tank pressure, vapor temperature, and liquid temperature predicted by the CFD model is validated against data from the MHTB spray-bar mixing experiment. Overall, the CFD models agree with experimental data, demonstrating their capability to simulate self-pressurization and pressure control processes in large-scale cryogenic storage tanks. These models can be valuable tools for designing and optimizing cryogenic fluid management systems in future applications.

Computational Fluid Dynamics↗

Modeling Self-Pressurization and Spray Bar Pressure Control of A Cryogenic Storage Tank in Normal Gravity

This paper presents computational fluid dynamics (CFD) models for simulating self-pressurization and spray-bar pressure control processes in a large-scale liquid hydrogen storage tank under normal gravity conditions. For self-pressurization, the model employs the kinetics-based Schrage equation alongside the volume-of-fluid (VOF) method to account for interfacial mass transfer. The CFD predictions of pressure and temperature are compared with experimental data from the Multipurpose Hydrogen Test Bed (MHTB) experiment, and the predicted interfacial mass transfer rates are also presented. A CFD model simulating pressure control using a spray bar has also been developed. An Eulerian-Lagrangian approach models the interactions between discrete droplets and the continuous ullage (vapor) phase. The spray model is coupled with the VOF method by tracking droplets in the ullage and removing them when they reach the liquid interface. The T-sat model calculates droplet-ullage heat and mass transfer, wherein droplets warm up to the saturation temperature corresponding to the ullage vapor pressure before evaporating while remaining at the saturation temperature. The evolution of tank pressure, vapor temperature, and liquid temperature predicted by the CFD model is validated against data from the MHTB spray-bar mixing experiment. Overall, the CFD models agree with experimental data, demonstrating their capability to simulate self-pressurization and pressure control processes in large-scale cryogenic storage tanks. These models can be valuable tools for designing and optimizing cryogenic fluid management systems in future applications.

Self-Pressurization↗

Multiple-objective Reinforcement Learning for Inverse Design and Identification

The aim of inverse chemical design is to develop new molecules with given optimized molecular properties or objectives. Recently, generative deep learning (DL) networks are considered as the state-of-the-art in inverse chemical design and have achieved early success in generating molecular structures with desired properties in the pharmaceutical and material chemistry fields. However, satisfying a large number (> 10 objectives) of molecular objectives is a limitation of current generative models. To improve the model’s ability to handle a large number of molecule design objectives, we developed a Reinforcement Learning (RL) based generative framework to optimize chemical molecule generation. Our use of Curriculum Learning (CL) to fine-tune the pre-trained generative network allowed the model to satisfy up to 21 objectives and increase the generative network’s robustness. The experiments show that the proposed multiple-objective RL-based generative model can correctly identify unknown molecules with an 83% to 100% success rate, compared to the baseline approach of 0%. Additionally, this proposed generative model is not limited to just chemistry research challenges; we anticipate that problems that utilize RL with multiple objectives will benefit from this framework.

reinforcement learning, generative model, inverse ↗

STUDY OF THE η'π 0 SYSTEM IN GLUEX

The η'π is an important decay channel for the potentially exotic hybrid meson π 1 (1600) that has been detected in the COMPASS, VES and E852 experiments. These previous experiments used a charged pion beam as a probe. In contrast, the GlueX experiment is designed to search for the exotic hybrid mesons using a linearly polarized photon beam. This thesis project analyzes the η'π 0 system produced in GlueX by the reaction γp → η'π 0 p. After optimizing the event selection to minimize background contributions, a mass independent partial wave analysis is performed in search of an exotic signature. Within the currently available statistical precision, no signal was found.

Dotel, Rupesh↗

High yield polar direct drive fusion neutron sources at the National Ignition Facility

Polar direct drive neutron source experiments were performed at the National Ignition Facility showing substantial improvement in total neutron yield and efficiency of conversion of laser energy to fusion output. Plastic capsules 3–4 mm in diameter were filled with 1.5 mg/cc of deuterium–tritium (DT) fuel and imploded with laser beam pointing and defocus designed to compensate for polar asymmetry introduced by the facility beam entrance angles. Radiation-hydrodynamics simulations were employed to optimize the multi-dimensional laser and target parameter space, within facility and target fabrication constraints. Ensembles of 1D simulations tuned to match the outputs of early shots in the series were used to design subsequent shots in the series. This allowed the later shots to be designed based on empirically motivated sensitivities to laser and target input parameters, while eliminating the need to explicitly model phenomena such as hydrodynamic instabilities and nonlinear laser–plasma interactions. Additionally, one experiment with a 3.0 mm diameter CH capsule produced 13.6 kJ (4.81 × 10 15 DT neutrons) from a laser input below the NIF optics damage threshold at 585 kJ, 328 TW. Two experiments with 4.0 mm capsules produced 31.3 and 33.6 kJ of fusion output (1.11 × 10 16 and 1.19 × 10 16 DT neutrons) with 1.10 MJ, 390 TW and 1.26 MJ, 425 TW of laser input, respectively.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Optimizing injection for the storage ring proton-EDM experiment

The proposed proton electric dipole moment (pEDM) experiment at Brookhaven National Laboratory (BNL), to be built inside the alternating gradient synchrotron (AGS) tunnel, aims to measure the proton’s electric dipole moment with a sensitivity of 10 −29 𝑒 cm. This paper presents the design of the injection line from the AGS booster to the pEDM storage ring, utilizing portions of the existing booster-to-AGS (BtA) transfer line. Building on the symmetric-hybrid lattice design [, Comprehensive symmetric-hybrid ring design for a proton-EDM experiment at below 10 −29 𝑒 cm, Phys. Rev. D 105, 032001 (2022)], our study emphasizes rigorous optics matching, detailed particle and spin tracking, and systematic error mitigation essential for achieving a target sensitivity of 10 −29 𝑒 cm. This design preserves the proton’s vertical spin orientation within ±20 mrad, a critical requirement for the pEDM measurement. Particle and spin tracking simulations using the ray-tracing code Zgoubi [F. Méot, Zgoubi users’ guide, Technical Report, Brookhaven National Laboratory (BNL), Relativistic Heavy Ion Collider (RHIC), Upton, NY, 2012] validate the design’s performance, demonstrating its feasibility for this precision experiment. The simulation results demonstrate that both clockwise (CW) and counterclockwise (CCW) injection lines meet the stringent beam envelope and polarization requirements.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Imprint of DESI fiber assignment on the anisotropic power spectrum of emission line galaxies

The Dark Energy Spectroscopic Instrument (DESI), a multiplexed fiber-fed spectrograph, is a Stage-IV ground-based dark energy experiment aiming to measure redshifts for 29 million Emission-Line Galaxies (ELG), 4 million Luminous Red Galaxies (LRG), and 2 million Quasi-Stellar Objects (QSO). The survey design includes a pattern of tiling on the sky, the locations of the fiber positioners in the focal plane of the telescope, and an observation strategy determined by a fiber assignment algorithm that optimizes the allocation of fibers to targets. This strategy allows a given region to be covered on average five times for a five-year survey, with a typical variation of about 1.5 about the mean, which imprints a spatially-dependent pattern on the galaxy clustering. In this study, we investigate the systematic effects of the fiber assignment coverage on the anisotropic galaxy clustering of ELGs and show that, in the absence of any corrections, it leads to discrepancies of order ten percent on large scales for the power spectrum multipoles. We introduce a method where objects in a random catalog are assigned a coverage, and the mean density is separately computed for each coverage factor. We show that this method reduces, but does not eliminate the effect. We next investigate the angular dependence of the contaminated signal, arguing that it is mostly localized to purely transverse modes. We demonstrate that the cleanest way to remove the contaminating signal is to perform an analysis of the anisotropic power spectrum P( k ,μ) and remove the lowest μ bin, leaving μ > 0 modes accurate at the few-percent level. Here, μ is the cosine of the angle between the line-of-sight and the direction of $\vec k$. Lastly, we also investigate two alternative definitions of the random catalog and show that they are comparable but less effective than the coverage randoms method.

79 ASTRONOMY AND ASTROPHYSICS↗

Optimization of Beidellite/Polyaniline Production Conditions by Central Composite Design for Removal of Acid Yellow 194

In the adsorption process, the adsorbent structure and its interaction with wastewater are the main determinant of the process efficiency. For this reason, the correct selection of the production conditions for the produced adsorbents is critical. In this study, the reaction time and the concentration of acid, oxidant, substrate, and monomer were selected as independent variables which effect the structure of the polyaniline based composite material. These production variables of polyaniline/beidellite (PANI/BEI) composites were designed by response surface methodology (RSM). According to RSM, 46 different PANI/BEI composites were synthesized and were used as an adsorbent in the removal of acid yellow 194. Thus, the optimum PANI/BEI production conditions were determined. After the identification of the optimum PANI/BEI production conditions, the effect of adsorption conditions such as pH, mixing time, and dye concentration were studied by batch experiments. The maximum adsorption capacity was obtained as 123 (mg g{sup −1}) at the T = 25 °C, t = 24 h, pH 3, m{sub s} = 0.15 g adsorbent, V{sub s} = 50 ml dye solution, and ω = 200 rpm. The results presented in this study revealed that the central composite design is a suitable method to optimize the production conditions of PANI/BEI and the prepared PANI/BEI composites has an important potential as an adsorbent for the removal of metal-complex dyes such as AY194. In addition, the polymerization of aniline and the removal of dye were confirmed by different analytical techniques such as BET, XRD, SEM, and EDAX.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

3D high-fidelity automated neutronics guided optimization of fusion blanket designs

The compact Fusion Pilot Plant (FPP) is defined in the recent National Academies of Sciences, Engineering, and Medicine report as the next step of fusion energy demonstration with a $50$ MWe peak net electricity production, $Q_e$ greater than $1$, and at least $3$ hours of continuous operation. This fusion pilot plant will be a test bed enabling materials, designs, and fuel management assessment, and it will represent an engineering challenge because of its high-fusion power and compact design targets. Previous reactor data is limited to experiments operating in different design space ranges. Therefore, design iterations and assessments should rely on high-fidelity first-principle theoretical and computational models. The high-fidelity integrated modeling of the plasma is a fundamental part of fusion energy research. However, the whole device modeling is often neglected, utilizing low-fidelity, system-level analysis. Recently, the need for high-fidelity multi-physics modeling was recognized, resulting in a selection of integrated tools. Further, autonomous design optimization requires a streamlined framework that perturbs the design point, reruns the analysis, and examines the outputs. However, high-fidelity analysis requires complex geometry specification that is difficult to perturb. This work presents the parametric CAD generation tool TRACER and a new neutronic workflow. TRACER allows the perturbation of the geometry representation, creating geometry files ready for further analysis. The streamlined neutronic workflow allows efficient and accurate calculations. The two new tools coupled together were used to perform a 3D high-fidelity multi-objective, multi-input optimization of an "ARC Class" compact tokamak design. The workflow was driven by an optimization driver for full automation.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Key metrics for HFIR HEU and LEU models

This report compares key metrics for two fuel design models of the High Flux Isotope Reactor (HFIR). The first model represents the highly enriched uranium (HEU) fuel currently in use at HFIR, and the second model considers a low-enriched uranium (LEU) interim design fuel. Except for the fuel region, the two models are consistent, and both include an experiment loading that is representative of HFIR's current operation. The considered key metrics are the neutron flux at the cold source moderator vessel, the mass of 252 Cf produced in the flux trap target region as function of cycle time, the fast neutron flux at locations of interest for material irradiation experiments, and the reactor cycle length. These key metrics are a small subset of the overall HFIR performance and safety metrics. They were defined as a means of capturing data essential for HFIR's primary missions, for use in optimization studies assessing the impact of HFIR's conversion from HEU fuel to different types of LEU fuel designs.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Microgravity Combustion Science and Fluid Physics Experiments and Facilities for the ISS

At the NASA Glenn Research Center, the Microgravity Science Program supports both ground-based and flight experiment research in the disciplines of Combustion Science and Fluid Physics. Combustion Science research includes the areas of gas jet diffusion flames, laminar flames, burning of droplets and misting fuels, solids and materials flammability, fire and fire suppressants, turbulent combustion, reaction kinetics, materials synthesis, and other combustion systems. The Fluid Physics discipline includes the areas of complex fluids (colloids, gels, foams, magneto-rheological fluids, non-Newtonian fluids, suspensions, granular materials), dynamics and instabilities (bubble and drop dynamics, magneto/electrohydrodynamics, electrochemical transport, geophysical flows), interfacial phenomena (wetting, capillarity, contact line hydrodynamics), and multiphase flows and phase changes (boiling and condensation, heat transfer, flow instabilities). A specialized International Space Station (ISS) facility that provides sophisticated research capabilities for these disciplines is the Fluids and Combustion Facility (FCF). The FCF consists of the Combustion Integrated Rack (CIR), the Fluids Integrated Rack (FIR) and the Shared Accommodations Rack and is designed to accomplish a large number of science investigations over the life of the ISS. The modular, multiuser facility is designed to optimize the science return within the available resources of on-orbit power, uplink/downlink capacity, crew time, upmass/downmass, volume, etc. A suite of diagnostics capabilities, with emphasis on optical techniques, will be provided to complement the capabilities of the subsystem multiuser or principal investigator-specific experiment modules. The paper will discuss the systems concept, technical capabilities, functionality, and the initial science investigations in each discipline.

Lauver, Richard W.↗

Application of Design of Experiments and Surrogate Modeling within the NASA Advanced Concepts Office, Earth-to-Orbit Design Process

Decisions made during early conceptual design have a large impact upon the expected life-cycle cost (LCC) of a new program. It is widely accepted that up to 80% of such cost is committed during these early design phases. Therefore, to help minimize LCC, decisions made during conceptual design must be based upon as much information as possible. To aid in the decision making for new launch vehicle programs, the Advanced Concepts Office (ACO) at NASA Marshall Space Flight Center (MSFC) provides rapid turnaround pre-phase A and phase A concept definition studies. The ACO team utilizes a proven set of tools to provide customers with a full vehicle mass breakdown to tertiary subsystems, preliminary structural sizing based upon worst-case flight loads, and trajectory optimization to quantify integrated vehicle performance for a given mission. Although the team provides rapid turnaround for single vehicle concepts, the scope of the trade space can be limited due to analyst availability and the manpower requirements for manual execution of the analysis tools. In order to enable exploration of a broader design space, the ACO team has implemented an advanced design methods (ADM) based approach. This approach applies the concepts of design of experiments (DOE) and surrogate modeling to more exhaustively explore the trade space and provide the customer with additional design information to inform decision making. This paper will first discuss the automation of the ACO tool set, which represents a majority of the development effort. In order to fit a surrogate model within tolerable error bounds a number of DOE cases are needed. This number will scale with the number of variable parameters desired and the complexity of the system's response to those variables. For all but the smallest design spaces, the number of cases required cannot be produced within an acceptable timeframe using a manual process. Therefore, automation of the tools was a key enabler for the successful application of an ADM approach to an ACO design study. Following the overview of the tool set automation, an example problem will be given to illustrate the implementation of the ADM approach. The example problem will first cover the inclusion of ground rules and assumptions (GR&A) for a study. The GR&A are very important to the study as they determine the constraints within which a trade study can be conducted. These trades must ultimately reconcile with the customer's desired output and any anticipated "what if" questions. The example problem will then illustrate the setup and execution of a DOE through the automated ACO tools. This process is accomplished more efficiently in this work by splitting the tools into two separate environments. The first environment encompasses the structural optimization and mass estimation tools, while the second is focused on trajectory optimization. Surrogate models are fit to the outputs of each environment and are "integrated" via connection of the surrogate equations. Throughout this process, checks are implemented to compare the output of the surrogates to the output of manually run cases to ensure that the error of the final surrogates is at an acceptable level. The conclusion of the example problem demonstrates the utility of the ADM based approach. Using surrogate models gives the ACO team the ability to visualize vehicle sensitivities to various design parameters and identify regions of interest within the design space. The ADM approach can thus be used to inform concept down selection and isolate promising vehicle configurations to be explored in more detail through the manual design process. In addition it provides the customer with an almost instantaneous turnaround on any ''what if" questions that may arise within the bounds of the surrogate model. This approach ultimately expands the ability of the ACO team to provide its customer with broad and rapid turnaround trade studies for launch vehicle conceptual design. The ability to identify a selection of designs which can meet the customer requirements will help ensure lower LCC of launch vehicle designs originating from ACO.

Zwack, Mathew R.↗

Application of Design of Experiments and Surrogate Modeling within the NASA Advanced Concepts Office, Earth-to-Orbit Design Process

Decisions made during early conceptual design have a large impact upon the expected life-cycle cost (LCC) of a new program. It is widely accepted that up to 80% of such cost is committed during these early design phases.1 Therefore, to help minimize LCC, decisions made during conceptual design must be based upon as much information as possible. To aid in the decision making for new launch vehicle programs, the Advanced Concepts Office (ACO) at NASA Marshall Space Flight Center (MSFC) provides rapid turnaround pre-phase A and phase A concept definition studies. The ACO team utilizes a proven set of tools to provide customers with a full vehicle mass breakdown to tertiary subsystems, preliminary structural sizing based upon worst-case flight loads, and trajectory optimization to quantify integrated vehicle performance for a given mission.2 Although the team provides rapid turnaround for single vehicle concepts, the scope of the trade space can be limited due to analyst availability and the manpower requirements for manual execution of the analysis tools. In order to enable exploration of a broader design space, the ACO team has implemented an Advanced Design Methods (ADM) based approach. This approach applies the concepts of Design of Experiments (DOE) and surrogate modeling to more exhaustively explore the trade space and provide the customer with additional design information to inform decision making. This paper will first discuss the automation of the ACO tool set, which represents a majority of the development e ort. In order to t a surrogate model within tolerable error bounds a number of DOE cases are needed. This number will scale with the number of variable parameters desired and the complexity of the system's response to those variables. For all but the smallest design spaces, the number of cases required cannot be produced within an acceptable timeframe using a manual process. Therefore, automation of the tools was a key enabler for the successful application of an ADM approach to an ACO design study. Following the overview of the tool set automation, an example problem will be given to illustrate the implementation of the ADM approach. The example problem will first cover the inclusion of Ground Rules and Assumptions (GR&A) for a study. The GR&A are very important to the study as they determine the constraints within which a trade study can be conducted. These trades must ultimately reconcile with the customer's desired output and any anticipated \what if" questions. The example problem will then illustrate the setup and execution of a DOE through the automated ACO tools. This process is accomplished more efficiently in this work by splitting the tools into two separate environments. The first environment encompasses the structural optimization and mass estimation tools, while the second is focused on trajectory optimization. Surrogate models are t to the outputs of each environment and are integrated via connection of the surrogate equations. Throughout this process, checks are implemented to compare the output of the surrogates to the output of manually run cases to ensure that the error of the final surrogates is at an acceptable level. The conclusion of the example problem demonstrates the utility of the ADM based approach. Using surrogate models gives the ACO team the ability to visualize vehicle sensitivities to various design parameters and identify regions of interest within the design space. The ADM approach can thus be used to inform concept down selection and isolate promising vehicle configurations to be explored in more detail through the manual design process. In addition it provides the customer with an almost instantaneous turnaround on any \what if" questions that may arise within the bounds of the surrogate model. This approach ultimately expands the ability of the ACO team to provide its customer with broad and rapid turnaround trade studies for launch vehicle conceptual design. The ability to identify a selection of designs which can meet the customer requirements will have the potential to lower LCC of launch vehicle designs originating from ACO.

Zwack, Mathew R.↗

Projected sensitivity of the SuperCDMS SNOLAB experiment

SuperCDMS SNOLAB will be a next-generation experiment aimed at directly detecting low-mass particles (with masses ≤ 10 GeV/c^2) that may constitute dark matter by using cryogenic detectors of two types (HV and iZIP) and two target materials (germanium and silicon). The experiment is being designed with an initial sensitivity to nuclear recoil cross sections ~1×10^-43 cm^2 for a dark matter particle mass of 1 GeV/c^2, and with capacity to continue exploration to both smaller masses and better sensitivities. The phonon sensitivity of the HV detectors will be sufficient to detect nuclear recoils from sub-GeV dark matter. A detailed calibration of the detector response to low-energy recoils will be needed to optimize running conditions of the HV detectors and to interpret their data for dark matter searches. Low-activity shielding, and the depth of SNOLAB, will reduce most backgrounds, but cosmogenically produced H-3 and naturally occurring Si-32 will be present in the detectors at some level. Even if these backgrounds are 10 times higher than expected, the science reach of the HV detectors would be over 3 orders of magnitude beyond current results for a dark matter mass of 1 GeV/c^2. The iZIP detectors are relatively insensitive to variations in detector response and backgrounds, and will provide better sensitivity for dark matter particles with masses ≳5 GeV/c^2. The mix of detector types (HV and iZIP), and targets (germanium and silicon), planned for the experiment, as well as flexibility in how the detectors are operated, will allow us to maximize the low-mass reach, and understand the backgrounds that the experiment will encounter. Upgrades to the experiment, perhaps with a variety of ultra-low-background cryogenic detectors, will extend dark matter sensitivity down to the “neutrino floor,” where coherent scatters of solar neutrinos become a limiting background.

Agnese, R.↗

Oak Ridge National Laboratory Neutron Spin Echo Beamline on NB-2

Neutron Spin Echo (NSE) spectroscopy uniquely measures the Q-dependence of slow relaxation dynamics, and having such a machine at HFIR will advance polarized neutron spectroscopy and promote the study of biophysical and energy materials using neutrons. The 2018 Instrument Advisory Board (IAB) advises Neutron Sciences Directorate, ORNL to upgrade the cold neutron delivery system at HFIR, addressing geometrical challenges in neutron transfer from the bright cold source. This is being optimized now: the entrance to the guide system is moving closer to the source, and more guides are being added. However, there are still significant challenges to making the cold flux at the sample world-class. With the proposed guide system, NB-2 can deliver more than 10 6 polarized neutrons per cm 2 /sec below 8Å, and probably 10Å with further optimization. With no potential for running user experiments with neutrons longer than 15Å, the utility of such a machine for biological studies is limited. However, there is a large demand for this class of spectrometer in materials science, chemical engineering, and nanotechnology. Workshops held over the past decade and the three-source vision have highlighted the community's need for a low-angle, high-energy resolution spectrometer at HFIR. A detailed design study of this spectrometer is needed, focusing on optimizing the neutron delivery system for SANS-type studies. This neutron spectrometer would complement studies already performed on both SNSNSE and BASIS by overlapping and extend the dynamic range accessible, while acknowledging the proposed machine, EXPANSE, at the Second Target Station. Two technologies currently exist for such a spectrometer: traditional DC solenoids like those on BL-15 at SNS and IN15 at the ILL, and RF-flipper-based machines similar to RESEDA at FRMII. Either instrument would satisfy the scientific justification. However, there are strong business and scientific cases to utilize the thermal flux, the resonant expertise developed at ORNL, and the potential to utilize an entangled beam of neutrons to probe quantum matter by adopting the neutron resonant spin-echo configuration.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗