TATB Thermal Decomposition: An Improved Kinetic Model for Explosive Safety Analysis
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Materials science, Chemistry - Chemical explosives↗
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Results for “Profiling optimization”
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BAO from angular clustering: optimization and mitigation of theoretical systematics
Here, we study the methodology and potential theoretical systematics of measuring Baryon Acoustic Oscillations (BAO) using the angular correlation functions in tomographic bins. We calibrate and optimize the pipeline for the Dark Energy Survey Year 1 dataset using 1800 mocks. We compare the BAO fitting results obtained with three estimators: the Maximum Likelihood Estimator (MLE), Profile Likelihood, and Markov Chain Monte Carlo. The fit results from the MLE are the least biased and their derived 1-$\sigma$ error bar are closest to the Gaussian distribution value after removing the extreme mocks with non-detected BAO signal. We show that incorrect assumptions in constructing the template, such as mismatches from the cosmology of the mocks or the underlying photo-$z$ errors, can lead to BAO angular shifts. We find that MLE is the method that best traces this systematic biases, allowing to recover the true angular distance values. In a real survey analysis, it may happen that the final data sample properties are slightly different from those of the mock catalog. We show that the effect on the mock covariance due to the sample differences can be corrected with the help of the Gaussian covariance matrix or more effectively using the eigenmode expansion of the mock covariance. In the eigenmode expansion, the eigenmodes are provided by some proxy covariance matrix. The eigenmode expansion is significantly less susceptible to statistical fluctuations relative to the direct measurements of the covariance matrix because of the number of free parameters is substantially reduced
79 ASTRONOMY AND ASTROPHYSICS↗
Parameter space mapping of the Princeton magnetorotational instability experiment
Extensive simulations of the Princeton Magnetorotational Instability (MRI) Experiment with the Spectral/Finite Element code for Maxwell and Navier-Stokes Equations (SFEMaNS) have been performed to map the MRI-unstable region as a function of inner cylinder angular velocity and applied vertical magnetic field. The angular velocities of the outer cylinder and the end-cap rings follow the inner cylinder in fixed ratios optimized for MRI. Here, we first confirm the exponential growth of the MRI linear phase using idealized conducting vertical boundaries (end caps) rotating differentially with a Taylor-Couette profile. Subsequently, we run a multitude of simulations to scan the experimental parameter space and find that the normalized volume-averaged mean-square radial magnetic field, our main instability indicator, rises significantly where MRI is expected. At various locations, the local radial components of fluid velocity and generated magnetic field are well correlated with the volume-averaged indicator. Based on this correlation, a diagnostic system that will measure the radial magnetic field at several locations on the inner cylinder is proposed as the main comparison between simulation and experiment. A detailed analysis of poloidal mode structures in the SFEMaNS code indicates that MRI, rather than Ekman circulation or Rayleigh instability, dominates the fluid behavior in the region where MRI is expected.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
High-throughput homogenization of a quasi-Gaussian ultrafast laser beam using a combined refractive beam shaper and spatial light modulator
Efficiently shaping femtosecond, transverse Gaussian laser beams to flat-top beams with flat wavefronts is critical for large-scale material processing and manufacturing. Existing beam shaping devices fall short either in final beam homogeneity or efficiency. Here, we present an approach that uses refractive optics to perform the majority of the beam shaping and then uses a fine-tune device (spatial light modulator) to refine the intensity profile. For the beam that we selected, circularly asymmetric with intensity fluctuations, our method achieved a uniformity of 0.055 within 90% of the beam area at 92% efficiency. The optimization involved an iterative beam shaping process that converged to optimum within 10 iterations.
43 PARTICLE ACCELERATORS↗
Going mobile to address emerging climate equity needs in the heterogeneous urban environment
We report the Brookhaven National Laboratory Center for Multiscale Applied Sensing (CMAS) aims to address environmental equity needs in the context of a changing climate. As a first step towards this goal, the center developed a one-of-a-kind observatory tailored to the study of highly heterogeneous urban environments. This article describes the features of the mobile observatory that enable its rapid deployment either on or off the power grid, as well as its instrument payload. Beyond its unique design, the observatory optimizes data collection within the obstacle-laden urban environment using a new smart sampling paradigm. This setup facilitated the collection of previously poorly documented environmental properties including wind profiles throughout the atmospheric column. The mobile observatory captured unique observations during its first few intensive observation periods (IOPs).. Vertical air motion and infrared temperature measurements collected along the faces of the supertall One Vanderbilt skyscraper in Manhattan, NY reveal how solar and anthropogenic heating affect wind flow and thus the venting of heat, pollution, and contaminants in urban street canyons. Also, air temperature measurements collected during travel along a 150-km transect between Upton and Manhattan, NY offer a high-resolution view of the urban heat island and reveal that temperature disparities also exist within the city across different neighborhoods. Ultimately, the datasets collected by CMAS are poised to help guide equitable urban planning by highlighting existing disparities and characterizing the impact of urban features on the urban microclimate with the goal of improving human comfort.
54 ENVIRONMENTAL SCIENCES↗
Durable and Low-Cost Fractal Structured Multifunctional Coatings for Next-Generation CSP
Fractal coatings on various low-cost and high-temperature metallic substrates such as SS316, SS347, In800H, In740H, In625, Haynes 230, etc. were fabricated employing our patented novel electrodeposition process at various deposition potentials and deposition times, as well as chemical etching. The best combination of the materials and processing conditions were co-optimized for the reliable and repeatable fabrication of the multifunctional coatings. Surface morphologies were examined using SEM and AFM, and fractal characterization was done using a 3D optical surface profiler. Fractal dimension was used to identify successful fabrication and material parameters. The mechanical durability of the coatings was evaluated using several standardized tests, such as sand abrasion (ASTM D968) and adhesion (ASTM D3359), to fully characterize and demonstrate the mechanical durability of the fabricated surfaces. HTF immersion tests on the fractal multifunctional coatings were conducted based on a modification of the ASTM D870, which is established for static water immersion testing. To calculate the corrosion rates and descaled weight loss of the samples subjected to thermal exposure for different time durations (100 h, 300 h, 500 h, and optionally 750 h) to estimate the corrosion rate. While protecting the substrates from corrosion is an important goal, an allied goals is also to examine the post-corrosion temperature stability and properties of the molten salts themselves due to the dissolution of the constituents of the alloys and the corrosion products from the coatings that cause “fouling” of the molten salts. Fouling characteristics of the different molten salt HTFs exposed to coated and uncoated substrates were investigated. Finally, considering a prototype molten salt/sCO2 heat exchanger, cost/performance model is developed to demonstrate that the coatings on low-cost alloys such as stainless steel provide lower levelized cost of heat exchanger compared to high nickel content Ha230.
14 SOLAR ENERGY↗
Rapid Screening of Liquid Metal Wetting for a Materials Compatibility Library
Wetting behavior of molten metals on solid substrates is a critical phenomenon influencing numerous industrial applications, including welding, anti-corrosion coatings, and metal additive manufacturing (AM). In particular, molten metal jetting (MMJ), an emerging AM technology, requires that the molten metal remain pinned at the nozzle exit. Thus, each new metal requires a specific nozzle material to ensure consistent droplet ejection and deposition, making it important to rapidly identify the appropriate wetting combinations. However, traditional measurements of wetting angles require expensive equipment and only allow one combination of materials to be investigated at a time which can be time consuming. This work introduces a rapid screening method based on sessile droplet experiments to evaluate wetting profiles across multiple metal–substrate combinations simultaneously. This study investigates the wetting interactions of molten Al alloy (Al4008), Cu, and Sn on various ceramic and metal substrates to identify optimal material combinations for MMJ nozzle designs. Results demonstrate that Al4008 achieves wetting on ceramic substrates such as AlN, TiO 2 , and SiC, with varying mechanisms including chemical reactions and weak surface interactions. Additionally, theoretical predictions regarding miscibility gaps and melting point differences were verified for Cu and Sn on refractory metals like Mo and W. Findings from this study contribute to the establishment of a materials compatibility library, enabling the selection of wetting/non-wetting combinations for stable MMJ operation. This resource not only advances MMJ technologies but also provides valuable insights for broader applications such as welding, coating, and printed electronics.
Materials science↗
Prediction of DIII-D Pedestal Structure from Externally Controllable Parameters
The sharp increase of pressure at the edge of a high confinement mode (H-mode) plasma, the pedestal, strongly impacts overall plasma performance. Predicting the pedestal is a necessity to control and optimize tokamak operations. An experimental data-driven machine learning (ML) approach is presented that predicts the pedestal heights and widths of electron density (ne) and electron temperature (Te) profiles as well as the separatrix ne from externally controllable parameters such as the plasma shape, heating method and power, and gas puff rate and integrated gas puff. The OMFIT framework was used with DIII-D data to efficiently, robustly, and automatically build a database of pedestal parameters to train machine learning models. Database creation was enabled by the search engine tool for DIII-D data, TokSearch, which parallelizes data fetching, enabling fast searches through basic signals of thousands of DIII-D shots and selection of relevant time intervals. Principal Component Analysis (PCA) separated the database into three clusters that represent classes of plasma shapes that are regularly used in DIII-D. The most important parameters for setting the pedestal structure were plasma current (Ip), toroidal magnetic field (Bφ), neutral beam heating power (PNBI) and shaping quantities. The Deep Jointly Informed Neural Networks (DJINN) algorithm was applied to identify suitable neural network (NN) architectures that appropriately capture the features of the pedestal database. Separate NNs were implemented for each pedestal parameter, and ensembling methods were used to improve the prediction accuracy and allowed estimation of the prediction uncertainty. The pedestal predictions of the test dataset lie within the measurement uncertainties of the pedestal parameters. The NN outperformed simple Linear Regression (LR) analysis, indicating non-linear dependencies in the pedestal structure. The presented achievements illustrate a promising path for future research, using feature extraction to infer experimental trends and thereby improve pedestal models as well as deploying NN for a fast pedestal prediction in DIII-D scenario development.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
Development and testing of a prototype mosaic wedge-and-strip anode detector
A preliminary laboratory study of a prototype mosaic wedge-and-strip anode, a new class of readout system that will furnish large format, high resolution microchannel plate detectors with comparatively simple readout electronics is described. The goals of this study were to demonstrate the linearity of the mosaic anode algorithm, and to verify the predicted resolution performance in a realistic detector configuration. It is found that the nonlinearity introduced at the boundary between two anodes is limited to 50-100 microns. It is also shown that the spatial resolution of the detector is limited mainly by partition noise to about 35 microns (FWHM) at a gain of 2 x 10 to the 7th. A systematic investigation of the charge distribution arriving at the anode is also described. Using the relative charges arriving on the two anodes of the mosaic pattern, the detailed shape of the distribution and its dependence on MCP-anode voltage, MCP voltage, and pulse height are determined. A significant dependence of the profile on pulse height, which can introduce a pulse height dependence to the centroid calculation, particularly near the anode edges is found. Improved anode designs which will achieve the optimal performance are discussed.
Rasmussen, A.↗
Algorithm for NO2 Vertical Column Retrieval from the Ozone Monitoring Instrument
We describe the operational algorithm for the retrieval of stratospheric, tropospheric, and total column densities of nitrogen dioxide NO2 from earthshine radiances measured by the Ozone Monitoring Instrument (OMI), aboard the EOS-Aura satellite. The algorithm uses the DOAS method for the retrieval of slant column NO densities. Air mass factors (AMFs) calculated from a stratospheric NO2 profile are used to make initial estimates of the vertical column density. Using data collected over a 24-h period, a smooth estimate of the global stratospheric field is constructed. Where the initial vertical column densities exceed the estimated stratospheric field, we infer the presence of tropospheric NO2, and recalculate the vertical column density (VCD) using an AMF calculated from an assumed tropospheric NO2 profile. The parameters that control the operational algorithm were selected with the aid of a set of data assembled from stratospheric and tropospheric chemical transport models. We apply the optimized algorithm to OMI data and present global maps of NO2 VCDs for the first time.
Bucsela, Eric J.↗
The Dawn of Geostationary Air Quality Monitoring: Case Studies from Seoul and Los Angeles
With the near-future launch of geostationary pollution monitoring satellite instruments over North America, East Asia, and Europe, the air quality community is preparing for an integrated global atmospheric composition observing system at unprecedented spatial and temporal resolutions. One of the ways that NASA has supported this community preparation is through demonstration of future space-borne capabilities using the Geostationary Trace gas and Aerosol Sensor Optimization (GeoTASO) airborne instrument. This paper integrates repeated high-resolution maps from GeoTASO, ground-based Pandora spectrometers, and low Earth orbit measurements from the Ozone Mapping and Profiler Suite (OMPS), for case studies over two metropolitan areas: Seoul, South Korea on June 9, 2016 and Los Angeles, California on June 27, 2017. This dataset provides a unique opportunity to illustrate how geostationary air quality monitoring platforms and ground-based remote sensing networks will close the current spatiotemporal observation gap. GeoTASO observes large differences in diurnal behavior between these urban areas, with NO2 accumulating within the Seoul Metropolitan Area through the day but NO2 peaking in the morning and decreasing throughout the afternoon in the Los Angeles Basin. In both areas, the earliest morning maps exhibit spatial patterns similar to emission source areas (e.g., urbanized valleys, roadways, major airports). These spatial patterns change later in the day due to boundary layer dynamics, horizontal transport, and chemistry. The nominal resolution of GeoTASO is finer than will be obtained from geostationary platforms, but when NO2 data over Los Angeles are up-scaled to the expected resolution of TEMPO, spatial features discussed are conserved. Pandora instruments installed in both metropolitan areas capture the diurnal patterns observed by GeoTASO, continuously and over longer time periods, and will play a critical role in validation of the next generation of satellite measurement. These case studies demonstrate that different regions can have diverse diurnal patterns and that day-to-day variability due to meteorology or anthropogenic patterns such as weekday/weekend variations in emissions is large. Low Earth orbit measurements, despite their inability to capture the diurnal patterns at fine spatial resolution, will be essential for intercalibrating the geostationary radiances and cross-validating the geostationary retrievals in an integrated global observing system.
Geostationary↗
Celestial Mapping System for Lunar Surface Mapping and Analytics
Celestial Mapping System (CMS) is a software platform to generate virtual 3D globe for celestial bodies within our solar system. Various layers are built on top of the virtual globe to provide visualization of high resolution imagery, enable precise measurements, build analytical capabilities and broad range of functionalities to assist planetary scientists and mission planners. CMS is built using OpenJDK 11 and will run on a wide variety of platforms such as Linux, Windows, OSX, etc. It has a thick client with less overhead to access hardware resources. This allows features such as terrain profiling and distance calculations to be performed on the client and on the fly. The present focus of CMS is on developing lunar mapping tool kits to provide features such as - 3D first person view with zoom and navigational capabilities, realistic terrain visualization based on LRO data, measurement tools, Apollo landing site annotations, stereoscopic view, elevation profiles, line of sight analysis and many more. The application is developed to provide situational and domain awareness on Lunar surface, planning capabilities for equipment placements and traverse path optimization. As data becomes available, CMS has the capabilities to integrate data sets that change dynamically in real-time, which will be useful for monitoring satellites and remotely-sensed data on Lunar surface. CMS utilizes NASA WorldWind Java library and OpenGL to achieve high-performance rendering of data and measurements, and also adheres to OGC standards. CMS supports importing synthetic features in a variety of 3D, 2D, vector and raster formats. Nomenclature is pulled from USGS Moon IAU2000 database, and lunar parameters are based of the standardized IAU2000 Moon ellipsoid. GDAL (Geospatial Data Abstraction Library) was used to modify and test the accuracy of datasets before integrating into the application. Our high-resolution global elevation model was compared with the LRO LOLA DEM elevation values and tested to ensure accuracy. Celestial Mapping System has several potential use cases for NASA including subsurface lava tubes visualization and analysis, soil analysis, resource visualization and representation on 3D globe.
GIS system↗
Peak Power Reduction for HVAC Operations in Multi-unit Commercial Buildings
The load profiles of most commercial consumers are characterized by brief periods of very high power consumption followed by intervals of relatively lower demand. In order to flatten commercial load profiles, several power utilities in addition to billing energy consumption, levy a demand charge (DC) on the monthly peak demand. In this work, we consider the problem of joint optimization of energy costs (EC) and DC incurred by a multi-unit building which follows a demand response (DR) program. Despite the non-linear structure of the problem, we show how the optimal solutions can be obtained efficiently using linear programming. We evaluate the performance of the proposed power control scheme for various climate zones in the US. We show that depending on the ambient conditions and the prescribed tariff structure, our strategy can result in savings of up to nearly 19% compared to the baseline.
Raza Naqvi, Syed A.↗
Network Optimization of the Electrosynthesis of Chemicals from CO2
Carbon dioxide electroreduction (ECO2R) is gaining attention due to its capacity to mitigate CO2 emissions while using electricity that would otherwise be curtailed. Its foreseeable industrial implementation requires of holistic methods to assess the technological and economic performance of ECO2R processes and integrate them in current chemical supply chains and power systems. Here, we combine techno-economic assessment and mathematical programming to find the optimal paths to electroreduce CO2 into valuable chemicals under variable electricity prices. The proposed approach is tested with a case study addressing the CO2 capture from flue gas or direct air and its electricity-powered reduction into carbon monoxide, formic acid or multi-carbon compounds. The results obtained demonstrate the ability of the framework to build ECO2R networks and provide operation profiles that respond to fluctuating electricity prices.
carbon dioxide↗
I/O Bottleneck Detection and Tuning: Connecting the Dots using Interactive Log Analysis
Using parallel file systems efficiently is a tricky problem due to inter-dependencies among multiple layers of I/O software, including high-level I/O libraries (HDF5, netCDF, etc.), MPI-IO, POSIX, and file systems (GPFS, Lustre, etc.). Profiling tools such as Darshan collect traces to help understand the I/O performance behavior. However, there are significant gaps in analyzing the collected traces and then applying tuning options offered by various layers of I/O software. Seeking to connect the dots between I/O bottleneck detection and tuning, we propose DXT Explorer, an interactive log analysis tool. In this paper, we present a case study using our interactive log analysis tool to identify and apply various I/O optimizations. We report an evaluation of performance improvement achieved for four I/O kernels extracted from science applications.
Bez, Jean Luca↗
Realization of a high luminosity muon beam at the Jefferson Lab
The proton is the major component of the visible matter of our universe, so being able to determine its fundamental properties, such as its charge radius, is of vital importance. In recent years, several experiments have been performed for the accurate measurement of the proton radius with different experimental techniques. The main and most common are based on two different techniques: ep scattering and Lamb shift spectroscopy of regular hydrogen atoms. The latter can also be performed on muonic hydrogen atoms with a significant improvement in accuracy. Recent measurements that use this method have highlighted a discrepancy between the results obtained with the diffusion of electrons and those obtained with the spectroscopic technique leading to the so-called ?proton radius puzzle?. The explanation of why this difference between the measured values exists is still a matter of discussion. The last attempt to address the puzzle was the PRad Experiment. It was performed with a unique experimental setup that gave the scientists an excellent control on the systematic errors that are usually present in electron-proton scattering experiments. This has significantly increased the precision of the measurement, bringing it in the same area as the spectroscopic ones done on muonic hydrogen atoms, which are considered the most precise. However, to solve the puzzle once and for all, even more precise electron scattering measurements are needed. Alternatively, new methods can be used, such as eg. muon-proton scattering at low transferred momenta in order to lower the systematic errors that comes with the measurement. This thesis tries to address this problem by studying the set up of an intense muon beam at the Jefferson Laboratory (JLab) that can be used to carry out a high-precision m ? p scattering experiment. Using Montecarlo simulations I studied the muon production resulting from the interaction of the primary electron beam with the beam-dump at JLab Hall-A. The simulations were performed using the FLUKA package via the FLAIR graphical interface. In this study, I modified an existing geometry (built for the ?Beam Dump eXperiment?) and performed several studies in order to optimize the muon beam parameters. In order to estimate the beam intensity, I studied the muon generation and transportation through the concrete bunker surrounding the Hall-A beam-dump. Detailed studies on muon attenuation and dispersion at different depth allowed me to track the beam profile in space and momentum as a function of the distance from the beam-dump. Last, but not least, I studied a possible tagging system for the muon beam. The tagging system will allow us to know with good precision (O(1=1000)) the energy of each muon of the beam. Based on the results obtained, I created an event generator that incorporates the detailed description of the muon beam (energy, position, emittance) useful to define and optimize the experimental setup for a future measurement of the proton radius at the JLab.
Fulci, Antonino↗
A two-stage stochastic optimization model for scheduling electric vehicle charging loads to relieve distribution-system constraints
Electric vehicles (EVs) hold promise to improve the energy efficiency and environmental impacts of transportation. However, widespread EV use can impose significant stress on electricity-distribution systems due to their added charging loads. This paper proposes a centralized EV charging-control model, which schedules the charging of EVs that have flexibility. This flexibility stems from EVs that are parked at the charging station for a longer duration of time than is needed to fully recharge the battery. The model is formulated as a two-stage stochastic optimization problem. The model captures the use of distributed energy resources and uncertainties around EV arrival times and charging demands upon arrival, non-EV loads on the distribution system, energy prices, and availability of energy from the distributed energy resources. We use a Monte Carlo-based sample-average approximation technique and an L-shaped method to solve the resulting optimization problem efficiently. We also apply a sequential sampling technique to dynamically determine the optimal size of the randomly sampled scenario tree to give a solution with a desired quality at minimal computational cost. Here, we demonstrate the use of our model on a Central-Ohio-based case study. We show the benefits of the model in reducing charging costs, negative impacts on the distribution system, and unserved EV-charging demand compared to simpler heuristics. Lastly, we also conduct sensitivity analyses, to show how the model performs and the resulting costs and load profiles when the design of the station or EV-usage parameters are changed.
33 ADVANCED PROPULSION SYSTEMS↗
Design Optimization of A-Type Heat Exchangers based on High Performance, Non-Round Tubes
Air-to-refrigerant heat exchangers (HXs) have been the topic of considerable research as they are the fundamental heat transfer components of HVAC&R systems. For residential and commercial applications, indoor heat exchangers are often in A-type configurations to reduce air-conditioner system footprint while still delivering the required cooling or heating. Classical HX design practices typically assume a uniform frontal air velocity profile to facilitate the use of conventional tube-fin airside heat transfer and pressure drop correlations for performance prediction. However, it is well-reported throughout the literature that A-type HXs experience significant airflow maldistribution which can severely degrade HX performance. Additionally, recent advancements in simulation software such as Computational Fluid Dynamics (CFD), Finite Element Analysis (FEA) and optimization algorithms have led researchers to consider primary heat transfer surface optimization to achieve highly compact HXs which do not require fins. In this paper, an A-type HX which utilizes shape-optimized non-round tubes is optimized for minimum duct size and airside pressure drop. This is achieved through coupling of an experimentally validated finite volume HX model with automated 2D CFD simulations of airflow through the HX for airside thermal-hydraulic performance evaluation. Preliminary results show that the optimal designs deliver similar capacity while achieving 20% reductions in airside pressure drop and duct cross-section area. Additionally, the optimal design apex angles in this study were similar to those from previous A-Type HX optimization studies for conventional tube-fin HX geometries, suggesting that the apex angle for optimal A-Type configuration performance may be independent of tube geometry.
42 ENGINEERING↗