Towards robust and scalable dispatch modeling of long-duration energy storage
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Guerra, Omar J.↗
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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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Modeled Results of Four Residential Energy Efficiency Measure Packages for Deriving Advanced Building Construction Research Targets
The Advanced Building Construction (ABC) Initiative from the U.S. Department of Energy Building Technologies Office is working to accelerate industrialized construction innovations for decarbonizing buildings. To inform performance and cost targets for research under the ABC Initiative, this analysis used the ResStock™ tool to evaluate the energy savings, utility bill impacts, and carbon emissions impacts of four simulated upgrade packages with specific target performance levels on a large sample of residential dwelling units (approximately 550,000) representative of the U.S. housing stock.
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
Hybrid Inverse Parameter Identification of Fully Coupled Ductile Damage Model for Steel Sheet DP600 with Two Different Algorithms: Trust Region and Genetic Algorithms
Ductile damage model has been widely regarded as a valuable method to predict the failure of sheet metal. Based on the thermodynamic theory and continuum damage mechanics, the fully coupled ductile damage model can be developed, which also can better predict the initiation and growth of the fracture. But the identifications of model parameters with theoretical methodology are difficult due to the complex coupling relationships existing among all state variables. The inverse methodology is regarded as a good method to resolve the problem. In this paper, the recently proposed fully coupled ductile damage model is chosen to investigate the deformation behavior of DP600 steel, in which the mixed saturation isotropic and kinematic hardenings are taken into account and fully coupled with the ductile damage. During the identification process, the least square formula of the error between experimental and numerical results is selected as the target function. The trust region algorithm and genetic algorithm are used with the help of MATLAB for the identification of three damage parameters. Finally, by comparing the experimental and numerical results, the validations of two algorithms are proved. The efficiency of the optimization process with trust region algorithm is higher, but with lower accuracy. Meanwhile, the optimization process is greatly affected by the chosen initial values of the ductile damage parameters.
36 MATERIALS SCIENCE↗
Adaptive/Nonadaptive Proton Radiation Planning and Outcomes in a Phase II Trial for Locally Advanced Non-small Cell Lung Cancer
Purpose: To analyze dosimetric variables and outcomes after adaptive replanning of radiation therapy during concurrent high-dose protons and chemotherapy for locally advanced non-small cell lung cancer (NSCLC). Methods and Materials: Nine of 44 patients with stage III NSCLC in a prospective phase II trial of concurrent paclitaxel/carboplatin with proton radiation [74 Gy(RBE) in 37 fractions] had modifications to their original treatment plans after re-evaluation revealed changes that would compromise coverage of the target volume or violate dose constraints; plans for the other 35 patients were not changed. We compared patients with adaptive plans with those with nonadaptive plans in terms of dosimetry and outcomes. Results: At a median follow-up of 21.2 months (median overall survival, 29.6 months), no differences were found in local, regional, or distant failure or overall survival between groups. Adaptive planning was used more often for large tumors that shrank to a greater extent (median, 107.1 cm{sup 3} adaptive and 86.4 cm{sup 3} nonadaptive; median changes in volume, 25.3% adaptive and 1.2% nonadaptive; P<.01). The median number of fractions delivered using adaptive planning was 13 (range, 4-22). Adaptive planning generally improved sparing of the esophagus (median absolute decrease in V{sub 70}, 1.8%; range, 0%-22.9%) and spinal cord (median absolute change in maximum dose, 3.7 Gy; range, 0-13.8 Gy). Without adaptive replanning, target coverage would have been compromised in 2 cases (57% and 82% coverage without adaptation vs 100% for both with adaptation); neither patient experienced local failure. Radiation-related grade 3 toxicity rates were similar between groups. Conclusions: Adaptive planning can reduce normal tissue doses and prevent target misses, particularly for patients with large tumors that shrink substantially during therapy. Adaptive plans seem to have acceptable toxicity and achieve similar local, regional, and distant control and overall survival, even in patients with larger tumors, vs nonadaptive plans.
62 RADIOLOGY AND NUCLEAR MEDICINE↗
A mathematical and numerical framework for the analysis of compressible thermal convection in gases at very high temperatures
The relevance of non-equilibrium phenomena, nonlinear behavior, gravitational effects and fluid compressibility in a wide range of problems related to high-temperature gas-dynamics, especially in thermal, mechanical and nuclear engineering, calls for a concerted approach using the tools of the kinetic theory of gases, statistical physics, quantum mechanics, thermodynamics and mathematical modeling in synergy with advanced numerical strategies for the solution of the Navier–Stokes equations. The reason behind such a need is that in many instances of relevance in this field one witnesses a departure from canonical models and the resulting inadequacy of standard CFD approaches, especially those traditionally used to deal with thermal (buoyancy) convection problems. Starting from microscopic considerations and typical concepts of molecular dynamics, passing through the Boltzmann equation and its known solutions, we show how it is possible to remove past assumptions and elaborate an algorithm capable of targeting the broadest range of applications. Moving beyond the Boussinesq approximation, the Sutherland law and the principle of energy equipartition, the resulting method allows most of the fluid properties (density, viscosity, thermal conductivity, heat capacity and diffusivity, etc.) to be derived in a rational and natural way while keeping empirical contamination to the minimum. Special attention is deserved as well to the well-known pressure issue. With the application of the socalled multiple pressure variables concept and a projection-like numerical approach, difficulties with such a term in the momentum equation are circumvented by allowing the hydrodynamic pressure to decouple from its thermodynamic counterpart. The final result is a flexible and modular framework that on the one hand is able to account for all the molecule (translational, rotational and vibrational) degrees of freedom and their effective excitation, and on the other hand can guarantee adequate interplay between molecular and macroscopic-level entities and processes. Performances are demonstrated by computing some incompressible and compressible benchmark test cases for thermal (gravitational) convection, which are then extended to the high-temperature regime taking advantage of the newly developed features.
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
Getting lost tracking the carbon footprint of hydropower
In the transition to low-carbon electricity, well-quantified estimates of carbon dynamics are needed to ensure that emissions reduction targets are achieved. Here we review the state of the science on carbon accounting for hydropower reservoirs and identify limitations and future solutions. Nearly all research on reservoir greenhouse-gas (GHG) emissions has focused on individual reservoirs in isolation without considering their position in a freshwater network draining organic matter from upstream watersheds or the coordinated operation of reservoir cascades. Second, carbon inventories have extrapolated from a small, non-probabilistic sample of highly variable measurements of GHG emissions to unsampled reservoirs. A stronger statistical foundation is needed to estimate a global inventory and its uncertainty. Third, attribution to hydropower is based on ranks assigned to reservoir purpose. Instead, the physical influence of hydropower on carbon dynamics could be directly measured. Fourth, current carbon-accounting practices neglect time. A time-varying approach would quantify variation in emissions for electricity portfolios from changes in the fuel mix at different times and account for ancillary services, i.e., the ability to support the grid when variable renewables are not available without using natural gas. Reservoirs also sequester a significant portion of inflowing carbon in sediments and slow the carbon cycle by delaying the return of carbon to the atmosphere for decades to centuries. Together, these refinements would help to illuminate pathways toward meeting energy demand with the longest-possible delay in returning carbon to the atmosphere and without adding ancient sources to the pool of carbon cycling through aquatic ecosystems.
13 HYDRO ENERGY↗
The Potential and Cost of Carbon Dioxide Removal Using Direct Air Capture with Land-Based Wind and Utility-Scale Photovoltaics
The rapid deployment of direct air capture and storage (DACS) is critical for achieving emission targets, necessitating precise evaluation of the scale and cost of carbon dioxide removal. This study examines the availability of land, electricity generation, and geologic CO 2 storage within the United States, estimating a technical potential for low-temperature, adsorbent-based DACS to remove approximately 9 gigatonnes of CO 2 annually. By 2050, a substantial portion of this removal could be achieved at net-removed costs below $\$$300/tonneCO 2 , though costs are highly variable depending on factors such as facility scale, construction expenses, climate-dependent productivity and heating efficiency, and geologic storage conditions. In the short term, DACS deployment will help identify key research priorities for advancing technology and reducing removal costs. Concurrently, there is an urgent need for scientifically robust and standardized frameworks for monitoring, reporting, and verifying DACS performance across both established and emerging technologies and energy sources.
Carbon capture↗
Measuring the Density of Different Materials by Using the Collimated Fast Neutron Beam
It was demonstrated in the previous work that various threat materials could be detected inside the sea going cargo container by measuring the three variables, carbon and oxygen concentration and density of investigated material. Density was determined by measuring transmitted neutrons, which is not always practical in terms of setting up the instrument geometry. In order to enable more geometry flexibility, we have investigated the possibility of using the scattered neutrons in cargo material identification. For that purpose, the densities of different materials were measured depending on the position of neutron detectors and neutron generator with respect to the target position. One neutron detector was put above the target, one behind and one in front of the target, above the neutron generator. It was shown that all three positions of neutron detectors can be successfully used to measure the target density, but only if the detected neutrons are successfully discriminated from the gamma rays. Although the associated alpha particle technique/associate particle imaging (API) was used to discriminate the neutrons from the gamma rays, it is believed that the same results would be obtained by using the pulse shape discrimination method. In that way API technique can be avoided and the neutron generator which produces much higher beam intensity than 10{sup 8} n/s can be used. (authors)
36 MATERIALS SCIENCE↗
NEON AOP Survey of Upper East River CO Watersheds: Waveform LiDAR Binary Data
The waveform Light Detection and Ranging (LiDAR) data in this package were generated through a National Ecological Observatory Network Airborne Observation Platform (NEON AOP) acquisition over watersheds of interest surrounding Crested Butte, Colorado. The remote sensing imagery acquired by the NEON AOP supports an interdisciplinary project on hydrology, biogeochemistry, and ecosystem functioning in a snow-dominated headwater environment. These waveform LiDAR data enable spatially continuous estimation of vegetation structure parameters to facilitate analyses of the major environmental drivers of structural and compositional variability. The package contains 97 compressed file archives in 7-zip (.7z) format, each corresponding to one acquisition flightpath. Within each .7z archive is a set of constituent files describing properties of the LiDAR waveforms, such as return intensity, geolocation, outgoing pulse and other behavior of the sensor and signals. Once downloaded, the files must first be unzipped using the widely distributed command-line software utility 7z, using the command '7z x \[filename\].7z \[target_directory\]'. All files within the .7z archives can be opened in IDL, MatLab, or the open-source R statistical computing environment. Further details about the data package are in the attached user guide (neon_aop_crbu_waveformlidar_userguide.pdf). This work was supported by the Watershed Function Science Focus Area at Lawrence Berkeley National Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231.
2018 NEON and 2025 CHESS Campaigns↗
Hawaii Utility Integration Initiatives to Enable Wind (Wind HUI) (Final Technical Report)
To advance the state and nation toward clean energy, Hawaii is pursuing an aggressive Renewable Portfolio Standard (RPS), 40% renewable generation and 30% energy efficiency and transportation initiatives by 2030. Additionally, with support from federal, state and industry leadership, the Hawaii Clean Energy Initiative (HCEI) is focused on reducing Hawaii's carbon footprint and global warming impacts. To keep pace with the policy momentum and changing industry technologies, the Hawaiian Electric Companies are proactively pursuing a number of potential system upgrade initiatives to better manage variable resources like wind, solar and demand-side and distributed generation alternatives (i.e. DSM, DG).
17 WIND ENERGY↗
ARM data-oriented metrics and diagnostics package for climate model evaluation (ARM-DIAGS-V3) version 3
A Python-based metrics and diagnostics package is currently being developed by the ARM Infrastructure Team at Lawrence Livermore National Laboratory to facilitate the use of long-term high frequency measurements from the ARM program in evaluating the regional climate simulation of clouds, radiation, precipitation, and aerosols. This metrics and diagnostics package computes climatological means of targeted climate model simulation and generates tables and plots for comparing the model simulation with ARM observational data. The CMIP model data sets are also included in the package to enable model inter-comparison as demonstrated in Zhang et al. (2018) and Zhang et al. (2020). The mean of the CMIP model can be served as a reference for individual models. Basic performance metrics are computed to measure the accuracy of mean state and variability of climate models. The evaluated physical quantities include cloud fraction, temperature, relative humidity, cloud liquid water path, total column water vapor, precipitation, sensible and latent heat fluxes, aerosol optical depth, and radiative fluxes, with plan to extend to more fields, such as the evaluation of model simulated aerosol physicochemical properties and cloud microphysics properties. Process-oriented diagnostics focusing on aerosol, cloud, and precipitation-related phenomena are also being developed for the evaluation and development of specific model physical parameterizations. In addition to the Southern Great Plains (SGP), North Slope of Alaska (NSA) and Tropical Western Pacific (TWP) atmospheric observatories in the ARMDIAGS version 2.0, the version 3.0 package have extended to the data collected at the ARM Eastern North Atlantic (ENA) atmospheric observatory and the Observation and Modeling of the Green Ocean Amazon (GOAMAZON) field campaign. The metrics and diagnostics package are currently built upon standard Python libraries and additional Python packages developed by DOE (CDAT). The ARM metrics and diagnostic package is available publicly with the hope that it can serve as an easy entry point for climate modelers to compare their models with ARM data. In this report, we first provide an overview of major metrics in section 2. The input data, which constitutes the core content of the metrics and diagnostics package, is summarized in section 3. A user's guide documenting the workflow/structure of the version 3.0 codes and including step-by-step instruction for running the package is described in section 4.
54 ENVIRONMENTAL SCIENCES↗
Microgrid Assisted Design for Remote Areas
In this work, we present a three-stage multiobjective mixed-integer linear programming (MILP) for the optimal expansion planning and operation of isolated multienergy microgrids in remote areas. By selecting the optimal distributed generators (DGs) and energy storage systems (ESSs) mix selection, siting, sizing, and scheduling in the remote microgrid, the proposed model is targeted to minimize the annualized total cost of microgrids while enhancing the performance of the system, i.e., minimizing the voltage deviations and line power loss. To represent the electricity and heat flow between generation resources and various electrical, heating, and cooling loads in the isolated microgrid, linearized power flow, and heat flow constraints are employed in the proposed optimization model. The available capacity of DGs and ESSs are modeled as discrete constants instead of continuous variables for practical purpose. Numerical simulation results on a remote microgrid consisting of DGs, ESSs, and various loads validate the proposed method.
24 POWER TRANSMISSION AND DISTRIBUTION↗
Xanthos-Lake Dataset
The Xanthos-Lake v1.0 dataset provides the input data, trained machine-learning models, and simulation outputs needed to characterize lake water balance, snow and ice conditions, and mixing-layer temperature within the Xanthos global hydrological modeling framework. The dataset supports lake representation across a wide range of lake sizes and hydroclimatic conditions by combining xLSIM, a basin-specific machine-learning emulator of lake snow, ice, ice-cover fraction, and mixing-layer temperature, with the Xanthos-Lake water-balance model. The archive contains NetCDF datasets used to train and evaluate xLSIM, trained model weights, processed meteorological and lake-property inputs, and basin- and lake-category-specific simulation outputs. These materials are organized into four primary data groups, described below. Snowice_model_inputs: Contains the NetCDF input data used to train xLSIM. The xLSIM machine-learning framework uses three lake-based datasets. The meteorological forcing dataset provides monthly relative humidity, specific humidity, surface wind speed, maximum and minimum air temperature, downward longwave and shortwave radiation, snowfall, surface air pressure, and total precipitation. Lake surface area is included as an additional static predictor. The target-state dataset provides lake ice thickness, snow depth, snow cover, and lake mixing-layer temperature, while a companion lake-surface dataset provides the lake ice-cover fraction. Before training, ice thickness and snow depth are converted from meters to centimeters, mixing-layer temperature is converted from kelvin to degrees Celsius and constrained to nonnegative values, and ice-cover fraction is converted from a fraction to a percentage. The predictor variables are normalized using statistics calculated across the selected lakes and time steps. Snowice_model_outputs: Contains the NetCDF outputs generated by xLSIM. For each basin, xLSIM produces a file containing observed and predicted lake-state variables for the training, validation, and testing periods. The modeled variables include lake ice thickness, snow depth, snow cover, mixing-layer temperature, and lake ice-cover fraction. For basins without a sufficiently persistent snow-and-ice signal, the emulator predicts only mixing-layer temperature. The outputs also include training and validation loss histories, the selected model configuration, identifiers of the lakes used in training, and SHAP-based feature-importance information at the global, lake, and seasonal-regime levels. The trained machine-learning model weights are provided separately within the dataset archive. Together, these files support model evaluation and subsequent coupling with the Xanthos-Lake water-balance framework. XanthosLAKES: Contains the NetCDF input data used by the Xanthos-Lake framework. Monthly meteorological inputs include relative and specific humidity, downward shortwave and longwave radiation, mean, maximum, and minimum air temperature, wind speed, precipitation, snowfall, and surface air pressure. Static lake-property datasets provide lake identifiers, geographic locations, surface area, volume, mean depth, elevation, drainage area, fetch, outlet-routing information, and associated Xanthos grid-cell attributes. Separate bathymetric datasets provide the coefficients of the area–depth and volume–depth relationships for each aggregated lake unit. GLEV-based records provide observed lake surface area and evaporation data used to initialize lake states, define reference conditions, and calibrate and evaluate the model. Xanthos-Lake Outputs: Contains the basin- and lake-category-specific NetCDF outputs generated by Xanthos-Lake. Monthly variables include lake surface area, storage volume, outlet discharge, evaporation rate, evaporation volume, lake–groundwater exchange, lake inflow, ice thickness, snow depth, snow-cover fraction, ice-cover fraction, and mixing-layer temperature. The files also contain lake-specific calibration and validation statistics, including normalized root-mean-square error, mean absolute error, Nash–Sutcliffe efficiency, Kling–Gupta efficiency, and percent bias. Stored calibrated and derived parameters include the weir discharge coefficient, fractional freeboard, groundwater exchange coefficient, reference water level, corresponding reference surface area and storage volume, weir-width adjustment factor, and the fraction of routed inflow entering the lake. Basin identifiers, lake category, simulation period, calibration and validation periods, and parameter-schema information are retained as NetCDF metadata.
Abeshu, Guta [Pacific Northwest National Laborator↗
Boundary Layer Transition Protuberance Tests at NASA JSC Arc-Jet Facility
A series of arc-jet tests in support of the Shuttle Orbiter Boundary Layer Transition flight experiment was conducted in the Channel Nozzle of the NASA Johnson Space Center Atmospheric Reentry Materials and Structures Facility. The boundary layer trip was a protrusion of a certain height and geometry fabricated as part of a 6"x6" tile insert, a special test article made of the Boeing Rigid Insulation tile material and coated with the Reaction Cured Glass used for the bottom fuselage tiles of the Space Shuttle Orbiter. A total of five such tile inserts were manufactured: four with the 0.25-in. trip height, and one with the 0.35-in. trip height. The tile inserts were interchangeably installed in the center of the 24"x24" variable configuration tile array mounted in the 24"x24" test section of the channel nozzle. The objectives of the test series were to demonstrate that the boundary layer trip can safely withstand the Space Shuttle Orbiter flight-like re-entry environments and provide temperature data on the protrusion surface, surfaces of the nearby tiles upstream and downstream of the trip, as well as the bond line between the tiles and the structure. The targeted test environments were defined for the tip of the protrusion, away from the nominal surface of the tile array. The arc jet test conditions were approximated in order to produce the levels of the free stream total enthalpy at the protrusion height similar to those expected in flight. The test articles were instrumented with surface, sidewall and bond line thermocouples. Additionally, Tempilaq temperature-indicating paint was applied to the nominal tiles of the tile array in locations not interfering with the protrusion trip. Five different grades of paint were used that disintegrate at different temperatures between 1500 and 2000 deg F. The intent of using the paint was to gauge the RCG-coated tile surface temperature, as well as determine its usefulness for a flight experiment. This paper provides an overview of the channel nozzle arc jet, test articles and test conditions, as well as the results of the arc-jet tests including the measured temperature response of the test articles, their pre- and post-test surface scans, condition of the thermal paint, and continents on the protrusion tip heating achieved in tests compared to the computational fluid dynamics predictions.
Larin, M. E.↗
Properties of Martian Hematite at Meridiani Planum by Simultaneous Fitting of Mars Mossbauer Spectra
Mossbauer spectrometers [1] on the two Mars Exploration Rovers (MERs) have been making measurements of surface rocks and soils since January 2004, recording spectra in 10-K-wide temperature bins ranging from 180 K to 290 K. Initial analyses focused on modeling individual spectra directly as acquired or, to increase statistical quality, as sums of single-rock or soil spectra over temperature or as sums over similar rock or soil type [2, 3]. Recently, we have begun to apply simultaneous fitting procedures [4] to Mars Mossbauer data [5-7]. During simultaneous fitting (simfitting), many spectra are modeled similarly and fit together to a single convergence criterion. A satisfactory simfit with parameter values consistent among all spectra is more likely than many single-spectrum fits of the same data because fitting parameters are shared among multiple spectra in the simfit. Consequently, the number of variable parameters, as well as the correlations among them, is greatly reduced. Here we focus on applications of simfitting to interpret the hematite signature in Moessbauer spectra acquired at Meridiani Planum, results of which were reported in [7]. The Spectra. We simfit two sets of spectra with large hematite content [7]: 1) 60 rock outcrop spectra from Eagle Crater; and 2) 46 spectra of spherule-rich lag deposits (Table 1). Spectra of 10 different targets acquired at several distinct temperatures are included in each simfit set. In the table, each Sol (martian day) represents a different target, NS is the number of spectra for a given sol, and NT is the number of spectra for a given temperature. The spectra are indexed to facilitate definition of parameter relations and constraints. An example spectrum is shown in Figure 1, together with a typical fitting model. Results. We have shown that simultaneous fitting is effective in analyzing a large set of related MER Mossbauer spectra. By using appropriate constraints, we derive target-specific quantities and the temperature dependence of certain parameters. By examining different fitting models, we demonstrate an improved fit for martian hematite modeled with two sextets rather than as a single sextet, and show that outcrop and spherule hematite are distinct. For outcrop, the weaker sextet indicates a Morin transition typical of well-crystallized and chemically pure hematite, while most of the outcrop hematite remains in a weakly ferromagnetic state at all temperatures. For spherule spectra, both sextets are consistent with weakly ferromagnetic hematite with no Morin transition. For both hematites, there is evidence for a range of particle sizes.
Agresti, D. G.↗
Formation acquisition sensor for the Terrestrial Planet Finder (TPF) mission
The Terrestrial Planet Finder (TPF) pre-project, an element of NASA’s Origins Program, is currently investigating multiple implementation architectures for finding earth-like planets around other stars. One of the technologies being developed is the Formation Flying Interferometer (FFI). The FFI is envisioned to consist of up to seven spacecraft, each with an infrared telescope, flying in precise formation within +/- l cm of pre-determined trajectories for synchronized observations. The spacecraft to- spacecraft separations are variable between 20 m to 100m during observations to support various interferometer configurations in the planet-finding mode. The challenges involved with TPF autonomous operations, ranging from formation acquisition and formation maneuvering, to high precision formation flying during science observations are unprecedented for deep space missions. To meet these challenges, the Formation Sensor Testbed (FST) under the TPF technology program will develop and demonstrate the key technology of the formation acquisition sensor. Key performance targets for the acquisition sensor are an instantaneous 4phi-steradian field of view and simultaneous range and bearing-angle measurements for multiple spacecraft with accuracy better than 50 cm and 1 degree, respectively. In this paper, we will describe the TPF FFI mission concept, the key formation flying challenges, the acquisition sensor design, the key design challenges, and the current plan to mitigate these design challenges.
Purcell, George H. Jr.↗
Defining a Metric to Assess Leachability of Contaminants from Cementitious Waste Forms in Lab Testing Related to Hanford - 20478
This paper reports on the determination of performance metrics for the release of four contaminants (technetium, iodine, nitrate, and chromium) from a theoretical supplemental low-activity waste (LAW) inventory of grout in the Hanford Integrated Disposal Facility (IDF). The performance metric was defined as a retardation factor, R, that can be used to quantify a waste form's ability to retain one contaminant compared with an un-retarded species (e.g., sodium). By setting the target R value at the magnitude required to maintain concentrations of the contaminants below the drinking water standard at the point of compliance for the IDF, a bar for grout leach performance can be established for screening laboratory leach test data. The R can be converted to a corresponding laboratory-observed diffusivity value against which to assess leach test data. The individual performance metrics were determined through an iterative set of simulations using a variable saturation and transport flow model of a grout waste form inventory in the IDF to calculate the resulting concentration-based requirements at the point of compliance. (authors)
12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
Performance and Commissioning of the BigBite Timing Hodoscope for Nucleon Form Factor Measurements at Jefferson Lab
The BigBite Timing Hodoscope detector is the primary subject of this thesis. The Super BigBite Spectrometer is a Jefferson Lab Hall A Collaboration project that has and will continue to measure nucleon electromagnetic form factors. This spectrometer includes the Timing Hodoscope which provides high resolution particle timing data for scattered electrons in the electron arm of BigBite. The Timing Hodoscope utilizes 90, 25 × 25 × 600 mm3 scintillator bars stacked on top of each other to form a single detector plane, and these bars are connected to 180 photo-multiplier tubes via light guides. Particles collide with the scintillating material creating a shower of optical photons and these particle events in the bars are collected to generate signals that are readout by the data acquisition (DAQ) electronics. NINO ASIC amplifier-discriminator cards output signals from the photo-multiplier tubes into analogue and logic signals, which are sent to analogue-to-digital (ADC) and time-to-digital (TDC) converter data acquisition readout modules. This data is then used for analysis of the detector. The focus of this thesis is the construction, commissioning, calibration, and performance of the BigBite Timing Hodoscope before and during the first of five nucleon electromagnetic form factor experiments at Jefferson Lab Hall A. Before the neutron magnetic form factor, G n M, experiment, cosmic ray data was collected during commissioning to confirm proper operation of the Timing Hodoscope electronics by observing the ADC and TDC data. Commissioning studies for charge normalization, gain matching, and other ADC and TDC detector data variables were performed before moving the detector into Hall A. Following installation in Hall A, several calibration studies were implemented to fine-tune the detector in preparation for use in the experiment. The calibration studies included analysis of timing cuts, TDC alignment, the time-walk effect, time difference offsets, and scintillator velocity corrections. Once the Timing Hodoscope was well-calibrated, data-taking during the experiment commenced and the beam-on-target data was used to characterize the Timing Hodoscope performance during the G n M experiment run-time. The performance analysis included studies observing energy deposit, cluster size, rates, accidentals, pile-up, tracking efficiency, position resolution, and time resolution. After application of physics cuts to ensure a data set comprised of particle tracks corresponding to elastic electrons, which is the main data of interest for measurement of G n M, the Timing Hodoscope is shown on average across all kinematic settings to have a >98% tracking efficiency, a position resolution of 4-6 cm in the non-dispersive plane and 1.5-2 cm in the dispersive plane, and a time resolution of 500-750 ps. These performance results are compared to a GEANT4 based performance simulation of the BigBite Timing Hodoscope for reference, showing to what degree the measured performance values match those taken from the simulation.
Marinaro, Ralph↗