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At least 235 records · Page 13

Jupiter's radiation belt ions - A comparison of theory and observation

Radial profiles are constructed for the Jovian radiation belt flux-tube content Y-asterisk from the reported phase-space density of energetic particles obtained from Voyager 1 data over the range L = 6 to L = 9. These experimental profiles are compared with theoretical solutions for Y-asterisk from an interchange-diffusion model of the coupled radiation belt and Iogenic ion populations. Subject to certain limitations of the Voyager 1 data, the model solutions are found to be consistent with the data for a variety of input parameters. Model solutions are also found corresponding to radiation belt ions that are expected to be mainly responsible for the auroral energy input. Comparison of the present theoretical profiles with the data implies that the energetic radiation belt ions should have a peak loss rate within a factor of three of that for strong diffusion scattering.

Summers, Danny↗

Modeling Landslide Susceptibility Over Large Regions with Fuzzy Overlay

Landslide susceptibility mapping is most effective if detailed surface and subsurface information can be combined with authoritative landslide catalogs or a deep understanding of local conditions. However, these types of homogeneous input data and catalogs are frequently not available over large areas. In this study, we model landslide susceptibility in Central America and the Caribbean islands by combining three globally available datasets and one regional dataset with fuzzy overlay. This primarily heuristic model provides the flexibility to test a range of different contributing variables and the capability to compare landslide inventories within the model framework that vary greatly in their size, spatiotemporal scope, and collection methods. We create a regional susceptibility map and evaluate its performance using receiver operating characteristics for both continuous and binned susceptibility values. This susceptibility map forms the basis for a near-real-time landslide hazard assessment system that couples susceptibility with rainfall and soil moisture triggers to estimate potential landslide activity at a regional scale. The application of this susceptibility model at the regional scale provides a foundation for transferring the methodology to other geographic areas.

Landslide↗

Modeling Variability of Plasma Conditions in the Io Torus

Telescopic observations an in situ measurements of the Io plasma torus show the density, temperature and composition to vary over time, sometimes up to a factor of 2. While previous models of the physical and chemical processes in the Io plasma torus have reasonably modeled the conditions of the Voyager 1 era, their authors have not addressed the observed variability nor explored the sensitivity of torus conditions to input parameters. In this paper we present a homogeneous torus model parameterized by five variables (transport timescale, neutral source strength, ratio of oxygen sulfur to atoms in the source, fraction of superthermal electrons, temperature of these hot electrons). The model incorporates the most recent data for ionization, recombination, charge exchange and radiative energy losses for the major torus species (S, S(sup +), S(sup ++), S(sup +++), O, O(sup +), O(sup ++). We solve equations of conservation of mass and energy to find equilibrium conditions for a set of input parameters. We compare model plasma conditions with those observed by Voyager 1 Voyager 2, and Cassini. Furthermore, we explore the sensitivity of torus conditions to each parameter. We find that (1) torus conditions are distinctly different for the Voyager 1, Voyager 2 and Cassini eras, (2) unique torus input parameters for any given era are poorly constrained given the wide range of solution space that is consistent with the range of observed torus conditions, (3) ion composition is highly sensitive to the specification of a non-thermal electron distribution, (4) neutral O/S source ratio is highly variable with model values ranging between 1.7 for Cassini to 4.0 for Voyager 1 conditions, (5) transport times range between 23 days for Voyager 2 to 50 days for Voyager 1 and Cassini, (6) neutral source strengths range between 7 to 30 x 10(sup -4) cm (sup -3) s(sup -1) which corresponds to a net production of 0.4 to 1.3 tons/s for a torus volume of 1.4 x 10(sup 31) cm(sup 3), or 38 R(sub j)(sup 3).

Delamere, P. A.↗

Improved Compression of Wavelet-Transformed Images

A recently developed data-compression method is an adaptive technique for coding quantized wavelet-transformed data, nominally as part of a complete image-data compressor. Unlike some other approaches, this method admits a simple implementation and does not rely on the use of large code tables. A common data compression approach, particularly for images, is to perform a wavelet transform on the input data, and then losslessly compress a quantized version of the wavelet-transformed data. Under this compression approach, it is common for the quantized data to include long sequences, or runs, of zeros. The new coding method uses prefixfree codes for the nonnegative integers as part of an adaptive algorithm for compressing the quantized wavelet-transformed data by run-length coding. In the form of run-length coding used here, the data sequence to be encoded is parsed into strings consisting of some number (possibly 0) of zeros, followed by a nonzero value. The nonzero value and the length of the run of zeros are encoded. For a data stream that contains a sufficiently high frequency of zeros, this method is known to be more effective than using a single variable length code to encode each symbol. The specific prefix-free codes used are from two classes of variable-length codes: a class known as Golomb codes, and a class known as exponential-Golomb codes. The codes within each class are indexed by a single integer parameter. The present method uses exponential-Golomb codes for the lengths of the runs of zeros, and Golomb codes for the nonzero values. The code parameters within each code class are determined adaptively on the fly as compression proceeds, on the basis of statistics from previously encoded values. In particular, a simple adaptive method has been devised to select the parameter identifying the particular exponential-Golomb code to use. The method tracks the average number of bits used to encode recent runlengths, and takes the difference between this average length and the code parameter. When this difference falls outside a fixed range, the code parameter is updated (increased or decreased). The Golomb code parameter is selected based on the average magnitude of recently encoded nonzero samples. The coding method requires no floating- point operations, and more readily adapts to local statistics than other methods. The method can also accommodate arbitrarily large input values and arbitrarily long runs of zeros. In practice, this means that changes in the dynamic range or size of the input data set would not require a change to the compressor. The algorithm has been tested in computational experiments on test images. A comparison with a previously developed algorithm that uses large code tables (generated via Huffman coding on training data) suggests that the data-compression effectiveness of the present algorithm is comparable to the best performance achievable by the previously developed algorithm.

Kiely, Aaron↗

Testing the Drop-Size Distribution-Based Separation of Stratiform and Convective Rain Using Radar and Disdrometer Data from a Mid-Latitude Coastal Region

Stratiform and convective rain are associated with different microphysical processes and generally produce drop-size distributions (DSDs) with different characteristics. Previous studies using data from (a) a tropical coastal location, (b) a mid-latitude continental location with semi-arid climate, and (c) a sub-tropical continental location, found that the two rain types could be separated in the NW–Dm space, where Dm is the mass-weighted mean diameter and NW is the normalized intercept parameter. In this paper, we investigate the same separation technique using data and observations from a mid-latitude coastal region. Three-minute DSDs from disdrometer measurements are used for the NW- versus Dm-based classification and are compared with simultaneous observations from an S-band polarimetric radar 38 km away from the disdrometer site. Specifically, RHI (range-height indicator) scans over the disdrometer were used for confirmation. Results show that there was no need to modify the separation criteria from previous studies. Three-minute DSDs from the same location were used as input to scattering calculations to derive retrieval equations for NW and Dm for the S-band radar using an improved technique and applied to the RHI scans to identify convective and stratiform rain regions. Two events are shown as illustrative examples.

Merhala Thurai↗

Implicit Large-Eddy Simulations of Compressible Mixing Layers

Implicit large-eddy simulations of the self-similar regions of two compressible mixing layers at high Reynolds number and convective Mach numbers of 0.381 and 0.690 were carried out. Experimental data was used as the input into a synthetic eddy method turbulent inflow boundary condition to initiate simulations. Computational grids with nearly isotropic cells were used and the grid counts ranged from 24 to 270 million points. Agreement with experimental velocity and Reynolds stress data was good given the simplifications of the simulation. The decrease in mixing layer growth rate with increasing compressibility compares well with the literature. Budgets for the Reynolds stress transport equation were extracted from the simulations. It was demonstrated that the grids used did not resolve the dissipation term at the experimental Reynolds number. However, low Reynolds number simulations indicate that the numerical dissipation replaces the physical dissipation and the dissipation term in the transport equation can be represented by the summation term that quantifies the imbalance in the budget. The budgets for the high Reynolds number mixing layers agree well with previous low Reynolds number studies; indicating that the primary mechanism for the reduced growth rate and increased anistropy of the Reynolds stress tensor due to compressibility is a reduction in the pressure-strain and production terms. A new scaling based on the magnitude of the Reynolds stress tensor is proposed. This scaling provides better relative comparisons between the data and shows that the decrease in pressure-strain in the shear component is the primary driver in reducing the transverse normal stress.

turbulence↗

A Framework for Multisector Scenarios of Outcomes for Well-Being and Resilience

Shared community scenarios of societal and environmental system changes have underpinned a broad range of research and assessment studies over the past several decades. These scenarios have largely aimed to address specific questions within broad issue areas like climate change or biodiversity and generally provided information on the drivers of change. The consequences of those drivers, such as impacts on society and policy responses, have tended to be left to the research community to investigate, using scenarios of drivers as inputs to their studies, producing projections of a disparate set of relevant output metrics. While this approach has had many benefits, it has fallen short of producing a robust, comparable literature describing outcomes across studies in common metrics. We argue that new scenarios are needed that extend current approaches to be organized around common outcome metrics for the well-being and resilience of society and ecosystems. We propose an approach that would focus on agreed upon outcomes for well-being and resilience as well as critical drivers of change, cut across issues and scales in multiple sectors, and draw on new systematic methods of scenario generation and discovery to highlight scenarios that are most critical in understanding societal risks and responding to them. Research derived from this outcome-based scenario development approach would facilitate improved assessment of risks of and responses to a range of stressors and the multi-sector interactions they generate.

54 ENVIRONMENTAL SCIENCES↗

Overdriven-detonation states produced by spherically diverging waves

A series of experiments are currently underway at the Detonation Science and Technology group, within Los Alamos National Laboratory, to study the overdriven-detonation states achievable in energetic materials as a result of detonation-wave interactions. A multi-component, energetic-material array was designed to study the amplification of velocity and pressure states produced by spherically diverging detonation waves in pentaerythritol tetranitrate (PETN) output charges. The unique geometry provides a low-jitter, highly controlled series of interactions between three independent-detonation inputs. Streak-camera imaging was performed on the output face of PETN pellets ranging in thickness from 2.5 – 10 mm to characterize the resulting breakout profile. Additionally, photonic Doppler velocimetry (PDV) measurements were collected at the output-pellet surface to determine simultaneity within the system. Detonation-wave velocities upwards of 16 mm/µs were measured, as compared to a steady-state detonation velocity of 7.9 mm/µs for the PETN pressing density investigated. Finally, additional experiments are being conducted to measure the pressure amplification generated at key areas of interaction.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Quantum efficiencies of imaging detectors with alkali halide photocathodes. I - Microchannel plates with separate and integral CsI photocathodes

Measurements and comparisons have been made of the quantum efficiencies of microchannel plate (MCP) detectors in the far-UV (below 2000-A) wavelength range using CsI photocathodes (a) deposited on the front surfaces of microchannel plates and (b) deposited on solid substrates as opaque photocathodes with the resulting photoelectrons input to microchannel plates. The efficiences were measured in both pulse-counting and photodiode modes of operation. Typical efficiencies are about 15 percent at 1216 A for a CsI-coated MCP compared with 65 percent for an opaque CsI photocathode MCP detector. Special processing has yielded an efficiency as high as 20 percent for a CsI-coated MCP. This may possibly be further improved by optimization of the tilt angle of the MCP channels relative to the front face of the MCP and incident radiation. However, at present there still remains a factor of at least 3 quantum efficiency advantage in the separate opaque CsI photocathode configuration.

Carruthers, George R.↗

Comparing Regional Energy Consumption for Direct Drone and Truck Deliveries

Drone delivery, once thought of as fictitious, is becoming a reality with the efforts of both forward-looking enterprises and supportive government policies. This emerging mode of e-commerce delivery raises many concerns. One important concern is the energy efficiency of direct delivery drones compared with conventional delivery trucks at a regional systems level. Here, in this study, we develop and apply methods to quantify the regional energy impacts of drone delivery, then we assess these impacts and compare them with the impacts of truck delivery. To study this problem, we develop an optimization model that determines an optimal set of fulfillment centers (FCs) with variable service capacities that allow drones to make direct e-commerce deliveries. We adopt two drone delivery energy estimation models from the literature and use them as inputs to demonstrate the potential range of energy needs. We also develop another optimization model to account for the energy consumption of diesel trucks (DTs) and battery electric vehicles (BEVs). We test the models using validated simulation data for the Chicago metropolitan area in the U.S. to quantify the energy implications of these three delivery modes. For drone delivery, we further extend our analyses by considering the impact of wind speed and flight patterns. Our results show that direct delivery drones require 15.8% more energy than BEVs on an average windy day, and they need 15% more energy than DTs on a very windy day. We provide essential parameter values for reproducibility and list relevant open problems.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Impact of Thermochromic Coatings on Thermal Management for Human Spacecraft Applications

Thermochromic variable emittance coatings (VECs) allow for passive, dynamic thermal management of space vehicles due to their temperature dependent optical properties. Ideally, a thermochromic material should exhibit low mid-IR emissivity for lower temperatures and switch to high mid-IR emissivity for higher temperatures; one promising material that demonstrates these characteristics is Lanthanum Strontium Manganite (LSM). The transition temperatures of LSM are dependent on the Lanthanum-to-Strontium ratio x, La1-xSrxMnO3. La0.8Sr0.2MnO3, which has an emittance of 0.5 for < 270 K, then a linear increase in emittance to 0.8 over an increase of 70 K where it will saturate at ~340K, is commonly utilized but this is tunable by changing the Sr concentration. The tunability of the transition temperature range of LSM motivates a need to understand the optimal thermal transition range for human spacecraft. Additionally, LSM has high solar absorptance and to combat this issue the VEC will be micropatterned on top of a highly solar reflective layer of Barium Sulfate (BaSO4). Consequently, this work will elucidate the tradeoffs between solar absorptance and variable emittance for this technology since the micropattern adversely couples the solar absorptance to the mid-IR emittance. This work develops a computational model using Thermal Desktop to study the utility of VECs on human spacecraft, such as Orion, subjected to mission phases such as lunar transit and Gateway docking. The model considers both external heat loads, from solar irradiation and planetary IR, as well as vehicle heat loads, from avionics and crew, as an input into the body mounted thermochromic radiators. There are several design targets for VECs, i.e. achieving the largest change in emittance, finding the optimal temperature range for the transition, and achieving the highest emittance in the high temperature phase. This work prioritizes these design targets for LSM to achieve the optimal heat rejection for a human spacecraft. The VECs are compared with static emittance coatings and the efficiency gains are quantified. Thermochromic VECs will ultimately lead to simplifications of active cooling systems which synergistically correlates to mass reduction and less energy consumption for space vehicles.

Joseph Peoples↗

Cosmological inference from an emulator based halo model. II. Joint analysis of galaxy-galaxy weak lensing and galaxy clustering from HSC-Y1 and SDSS

Here, we present high-fidelity cosmology results from a blinded joint analysis of galaxy-galaxy weak lensing (ΔΣ) and projected galaxy clustering (w p ) measured from the Hyper Suprime-Cam Year-1 (HSC-Y1) data and spectroscopic Sloan Digital Sky Survey (SDSS) galaxy catalogs in the redshift range 0.15 < z < 0.7. We define luminosity-limited samples of SDSS galaxies to serve as the tracers of w p in three spectroscopic redshift bins, and as the lens samples for ΔΣ. For the ΔΣ measurements, we select a single sample of 4×10 6 source galaxies over 140 deg 2 from HSC-Y1 with photometric redshifts (photo z) greater than 0.75, enabling a better handle of photo- z errors by comparing the ΔΣ amplitudes for the three lens redshift bins. The deep, high-quality HSC-Y1 data enable significant detections of the ΔΣ signals, with integrated signal-to-noise ratio S/N ~ 15 in the range 3 ≤ R/[h –1 Mpc] ≤ 30 for the three lens samples, despite the small area coverage. For cosmological parameter inference, we use an input galaxy-halo connection model built on the dark emulator package (which uses an ensemble set of high-resolution N-body simulations and enables fast, accurate computation of the clustering observables) with a halo occupation distribution that includes nuisance parameters to marginalize over modeling uncertainties. We model the ΔΣ and wp measurements on scales from R≃3 and 2h –1 Mpc , respectively, up to 30 h –1 Mpc (therefore excluding the baryon acoustic oscillations information) assuming a flat Λ CDM cosmology, marginalizing over about 20 nuisance parameters and demonstrating the robustness of our results to them. With various tests using mock catalogs described in Miyatake et al. [preceding paper, Phys. Rev. D 106, 083519 (2022)], we show that any bias in the clustering amplitude S 8 ≡ σ 8 (Ω m /0.3) 0.5 due to uncertainties in the galaxy-halo connection is less than ~ 50 % of the statistical uncertainty of S 8 , unless the assembly biaseffect is unexpectedly large. Our best-fit models have S 8 = 0.795$_{-0.042}^{+0.049}$ (mode and 68% credible interval) for the flat Λ CDM model; we find tighter constraints on the quantity S 8 (α = 0.17)≡σ 8 (Ω m /0.3) 0.17 = 0.745$_{-0.031}^{+0.039}$.

79 ASTRONOMY AND ASTROPHYSICS↗

Comparative Modelling of the Spectra of Cool Giants

Our ability to extract information from the spectra of stars depends on reliable models of stellar atmospheres and appropriate techniques for spectral synthesis. Various model codes and strategies for the analysis of stellar spectra are available today. Aims. We aim to compare the results of deriving stellar parameters using different atmosphere models and different analysis strategies. The focus is set on high-resolution spectroscopy of cool giant stars. Methods. Spectra representing four cool giant stars were made available to various groups and individuals working in the area of spectral synthesis, asking them to derive stellar parameters from the data provided. The results were discussed at a workshop in Vienna in 2010. Most of the major codes currently used in the astronomical community for analyses of stellar spectra were included in this experiment. Results. We present the results from the different groups, as well as an additional experiment comparing the synthetic spectra produced by various codes for a given set of stellar parameters. Similarities and differences of the results are discussed. Conclusions. Several valid approaches to analyze a given spectrum of a star result in quite a wide range of solutions. The main causes for the differences in parameters derived by different groups seem to lie in the physical input data and in the details of the analysis method. This clearly shows how far from a definitive abundance analysis we still are.

stars↗

A Generalized Dual-Frequency Ratio (DFR) Approach for Rain Retrievals

The dual-frequency ratio of radar reflectivity factors (DFR) has been shown to be a useful quantity as it is independent of the number concentration of the particle size distribution and primarily a function of the mass-weighted particle diameter, Dm. A drawback of DFR-related methods for rain estimation, however, is the non-unique relationship between Dm and DFR. At Ku- and Ka-band frequencies, two solutions for Dm exist when DFR is less than zero. This ambiguity generates multiple solutions for the range profiles of the particle size parameters. We investigate characteristics of these solutions for both the initial-value (forward) and final-value (backward) forms of the equations. To choose one of among many possible range profiles of Dm, number concentration and rain rate, R, independently measured path attenuations are used. For the backward approach the possibility exists of dispensing with externally measured path attenuations by achieving consistency between the input and output path attenuations. The methods are tested by means of a simulation based on disdrometer-measured raindrop size distributions and the results are compared with a simplified version of the operational R-Dm method.

Robert Meneghini↗

Probabilistic Assessment and Uncertainty Analysis of CO2 Storage Capacity of the Morrow B Sandstone—Farnsworth Field Unit

This paper presents probabilistic methods to estimate the quantity of carbon dioxide (CO2) that can be stored in a mature oil reservoir and analyzes the uncertainties associated with the estimation. This work uses data from the Farnsworth Field Unit (FWU), Ochiltree County, Texas, which is currently undergoing a tertiary recovery process. The input parameters are determined from seismic, core, and fluid analyses. The results of the estimation of the CO2 storage capacity of the reservoir are presented with both expectation curve and log probability plot. The expectation curve provides a range of possible outcomes such as the P90, P50, and P10. The deterministic value is calculated as the statistical mean of the storage capacity. The coefficient of variation and the uncertainty index, P10/P90, is used to analyze the overall uncertainty of the estimations. A relative impact plot is developed to analyze the sensitivity of the input parameters towards the total uncertainty and compared with Monte Carlo. In comparison to the Monte Carlo method, the results are practically the same. The probabilistic technique presented in this paper can be applied in different geological settings as well as other engineering applications.

03 NATURAL GAS↗

Experimentally-determined external heat loss of automotive gas turbine engine

An external heat balance was conducted on a 150 HP two-shaft automotive gas turbine engine. The engine was enclosed in a calorimeter box and the temperature change of cooling air passing through the box was measured. Cooling airflow ranges of 1.6 to 2.1 lb-per-second and 0.8 to 1.1 lb-per-second were used. The engine housing heat loss increased as the cooling airflow through the calorimeter box was increased, as would be the case in a moving automobile. The heat balance between the total energy input and the sum of shaft power output and various losses compared within 30 percent at engine idle speeds and within 7 percent at full power.

Meng, P. R.↗

First-Order-hold interpolation digital-to-analog converter with application to aircraft simulation

Those who design piloted aircraft simulations must contend with the finite size and speed of the available digital computer and the requirement for simulation reality. With a fixed computational plant, the more complex the model, the more computing cycle time is required. While increasing the cycle time may not degrade the fidelity of the simulated aircraft dynamics, the larger steps in the pilot cue feedback variables (such as the visual scene cues), may be disconcerting to the pilot. The first-order-hold interpolation (FOHI) digital-to-analog converter (DAC) is presented as a device which offers smooth output, regardless of cycle time. The Laplace transforms of these three conversion types are developed and their frequency response characteristics and output smoothness are compared. The FOHI DAC exhibits a pure one-cycle delay. Whenever the FOHI DAC input comes from a second-order (or higher) system, a simple computer software technique can be used to compensate for the DAC phase lag. When so compensated, the FOHI DAC has (1) an output signal that is very smooth, (2) a flat frequency response in frequency ranges of interest, and (3) no phase error. When the input comes from a first-order system, software compensation may cause the FOHI DAC to perform as an FOHE DAC, which, although its output is not as smooth as that of the FOHI DAC, has a smoother output than that of the ZOH DAC.

Cleveland, W. B.↗

Hydrogen Leak Modeling for Development of Smart Distributed Monitoring Under Unintended Releases

Hydrogen is a versatile and clean energy carrier that can be produced from various renewable sources such as wind, solar, and hydropower. Hydrogen has the potential to play a crucial role in decarbonizing industrial processes that are currently reliant on fossil fuels and provide long-duration and/or seasonal energy storage to enable electricity decarbonization. Hydrogen can also be used as a fuel for fuel cell vehicles, providing a zero-emission alternative to traditional internal combustion engines. DOE launched the Hydrogen Energy Earthshot (Hydrogen Shot) in June 2021 to reduce the cost of clean hydrogen by 80% to $1 per 1 kilogram in 1 decade ("1 1 1"). While promising, Hydrogen is highly-flammable, and in the presence of oxygen, it can form explosive mixtures. . Therefore, understanding leak scenarios is essential to evaluate and mitigate the safety risks associated with potential hydrogen leaks. An increased understanding of leak behavior, and having tools to model leaks, can help assess how hydrogen would disperse in different environments, influencing emergency response plans and safety measures, and identify potential issues with materials and design systems that can withstand the challenges posed by hydrogen. Recently, researchers have attempted to study hydrogen leaks for development of risk management strategies. However, the focus has been on closed or semi-closed spaces like storage rooms, vehicles, garages, and fueling stations - all promising locations for future hydrogen infrastructure. In this presentation, the modeling environment extends the span of research further by modeling hydrogen leak in an outdoor, open space. We will present the key challenges with modeling hydrogen leaks in an uncontrollable environment, how they were handled, and how modeling results informed sensor selection and placement. A Hydrogen research facility at the National Renewable Energy Laboratory (NREL) was used as a case study to model hydrogen leaks. In the future, Hydrogen wide area detection methodologies will be developed and tested at this site to monitor for unintended and operational hydrogen releases. The data generated from modeling will be used to develop a predictive model to detect hydrogen leak location based on concentration measured by sensors in this open space. Furthermore, the facility was also chosen because controlled hydrogen releases can be performed. A computational fluid dynamics (CFD) based modeling approach was taken to model hydrogen leak. The full-scale hydrogen facility was modeled with a large ambient domain. The electrolyzer at the facility can produce a controlled release rate of 27 kg-H2/hr. Site-specific atmospheric and weather condition data such as wind direction, wind speed at various altitudes, and temperature were used as inputs to the model. To capture the variability of weather conditions, a subset of the weather conditions experienced during daytime hours without precipitation over the course of three months was generated; using established data clustering techniques, a total of 100 condition sets were chosen. The results show statistical distributions and ranges of hydrogen concentrations at locations throughout the domain. These distributions are compared to experimental data from a constant mass flow, controlled hydrogen release at the facility. The stochastic wind conditions of the release make direct validation difficult, therefore, statistical comparison approaches were used. Wind conditions are found to significantly impact the release behavior, including direction and concentration. Sensor selection and placement is proposed for the facility and is now based on release behavior predicted for the facility given its weather patterns; this is much more informed than without the modeling results. The methodology and analysis procedure can be translated to other facilities using modified geometries and site-specific weather conditions. Hydrogen holds great promise as a renewable energy fuel, but ensuring safety in its production, storage, and use is paramount. Studying potential leak scenarios in an open space will help develop sensors to detect hydrogen on a large spectrum of concentration and eventually build a smart distributed monitoring system.

CFD↗