Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Averages”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 451 records · Page 25
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Representative Phenomena of Cyclic Turbulent Combustion in High-Pressure Fuel Sprays

Abstract Cyclic variations in conventional diesel combustion engines can lead to large differences in engine out emissions even at steady operation. This study uses an optically accessible constant-pressure flow chamber to acquire fuel injections in quick succession to analyze mixing, auto-ignition, and combustion of diesel-surrogate n-heptane using multiple high-speed optical diagnostics. Prior studies have utilized fewer injections and/or they rely on analysis of ensemble average behavior. These approaches do not yield information on injection-to-injection variation or provide confidence in utilizing individual injection measurements for high-fidelity computational fluid dynamics(CFD) model validation. In this study, a large set of 500 injections is used to obtain global parameters including liquid length, vapor penetration length, ignition delay time, and lift-off length. Results for multiple injections are presented to illustrate large injection to injection variations. Potential sources for these variations are analyzed to conclude localized, small scale turbulence and rate of injection variations as the likely sources. Then, a statistical method based on z-scores is proposed and implemented to identify instantaneous injections that best represent the bulk data-set of jet boundaries measured independently by three different diagnostics. This synthesis of statistics-guided screening of data set and ensemble-average analysis offers higher confidence for CFD model validation relying upon both a representative single and average injection results.

42 ENGINEERING↗
DOE OSTI2024

Microstructural evolution in a precipitate-hardened (Fe 0.3 Ni 0.3 Mn 0.3 Cr 0.1 ) 94 Ti 2 Al 4 multi-principal element alloy during high-pressure torsion

Multi-principal element alloys demonstrate high strength, thermal stability, and irradiation resistance, making them excellent candidate materials for applications in nuclear reactors and other harsh environments. Some studies have examined the use of high-pressure torsion to strengthen MPEAs through grain size reduction and strain hardening. However, no studies have investigated the effect of HPT on secondary phases (precipitates) within an MPEA. Two alloys, (Fe 0.3 Ni 0.3 Mn 0.3 Cr 0.1 ) 94 Ti 2 Al 4 containing Ni(Ti, Al) B2 phase, and CrFe σ phase, and single-phase Fe 0.3 Ni 0.3 Mn 0.3 Cr 0.1 , were fabricated by casting and heat treatment. Both alloys were then processed with HPT to study microstructural evolution. Scanning electron microscopy (SEM) and transmission electron microscopy (TEM) were used to characterize the alloys before and after HPT processing. HPT processing produced a nanocrystalline structure in both alloys, but (Fe 0.3 Ni 0.3 Mn 0.3 Cr 0.1 ) 94 Ti 2 Al 4 exhibited a significantly smaller grain size and higher dislocation density than Fe 0.3 Ni 0.3 Mn 0.3 Cr 0.1 , with corresponding higher hardness. Before HPT, the (Fe 0.3 Ni 0.3 Mn 0.3 Cr 0.1 ) 94 Ti 2 Al 4 alloy consisted of large grain (~ 400 μm) and precipitates, including B2 of ~ 38 μm average size, B2 of ~ 0.7 μm average size, and small amounts of σ of ~ 1.5 μm average size. After HPT, the larger B2 precipitates were decreased in size and volume fraction, while the smaller B2 precipitates were completely dissolved; the σ precipitates appeared unaffected by HPT, likely due to their much higher hardness. Finally, observation of the B2 precipitate distribution along radial distance indicates that the strain caused the precipitates to fracture at intermediate strain (γ = 125) and dissolve at high strain (γ = 280).

36 MATERIALS SCIENCE↗
DOE OSTI2025

Graph decomposition techniques for solving combinatorial optimization problems with variational quantum algorithms

The quantum approximate optimization algorithm (QAOA) has the potential to approximately solve complex combinatorial optimization problems in polynomial time. However, current noisy quantum devices cannot solve large problems due to hardware constraints. In this work, we develop an algorithm that decomposes the QAOA input problem graph into a smaller problem and solves MaxCut using QAOA on the reduced graph. The algorithm requires a subroutine that can be classical or quantum—in this work, we implement the algorithm twice on each graph. One implementation uses the classical solver Gurobi in the subroutine and the other uses QAOA. We solve these reduced problems with QAOA. On average, the reduced problems require only approximately 1/10 of the number of vertices than the original MaxCut instances. Furthermore, the average approximation ratio of the original MaxCut problems is 0.75, while the approximation ratios of the decomposed graphs are on average of 0.96 for both Gurobi and QAOA. With this decomposition, we are able to measure optimal solutions for ten 100-vertex graphs by running single-layer QAOA circuits on the Quantinuum trapped-ion quantum computer H1-1, sampling each circuit only 500 times. This approach is best suited for sparse, particularly k-regular graphs, as k-regular graphs on n vertices can be decomposed into a graph with at most $\frac{nk}{k+1}$ vertices in polynomial time. Further reductions can be obtained with a potential trade-off in computational time. In conclusion, while this paper applies the decomposition method to the MaxCut problem, it can be applied to more general classes of combinatorial optimization problems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Interlaboratory Reproducibility of Contour Method Data Analysis and Residual Stress Calculation

While the contour method for residual stress assessment has developed rapidly, no published study documents its interlaboratory reproducibility. Objective: Here we report an initial reproducibility experiment focused on contour method data analysis and residual stress calculation. The experiment uses surface topography data from a physical process simulation of elastic-plastic beam bending. The simulation provides surface topography, for input to the contour method data analysis, as well as a known residual stress field with 130 MPa peak magnitude. Additionally, to increase realism, noise and specific artifacts are added to the topography data. A group of participants received the topography data (without the known residual stress), independently analyzed the data, and submitted results as a two-dimensional residual stress field. Analysis of submissions provides a group average residual stress field and the spatial distribution of reproducibility standard deviation. The group average residual stress agrees with the known stress in magnitude and spatial trend. The reproducibility standard deviation ranges from 2 to 54 MPa over the measurement plane, with an average of 5.4 MPa. Reproducibility standard deviation is smaller in the cross-section interior (≤ 5 MPa), modest near local extrema in the stress field (5 to 10 MPa), and larger near the cross-section boundaries (10 to 30 MPa). Overall, the largest values of reproducibility standard deviation (up to 54 MPa) occur in limited areas where artifacts had been added to the topography data; while some participants identified and removed these artifacts, some did not, leading to systematic differences that elevated the standard deviation.

42 ENGINEERING↗
DOE OSTI2025

Evaluation and calibration of MERRA-2 and CAMS reanalysis for PM 2.5 in a semi-urbanized area in the south of the Amazon

Air pollution has significant implications for the climate and poses irreversible risks to human health. The Amazon region of Brazil is severely affected by biomass burning (BB) emissions, yet air quality monitoring remains highly inadequate. Given the scarcity of surface-based observations, reanalysis models have become essential tools for assessing air pollution. Although MERRA-2 and CAMS PM 2.5 products are widely utilized, their validation and comprehensive evaluation for the Amazon Basin remain limited. Here, this study assesses the performance of these products in a semi-urbanized region in the southern Amazon. The calibrated time series was employed to analyze PM 2.5 concentrations from 2003 to 2023. Our results showed satisfactory performance of both products for the 24-h averages of PM 2.5 , with linear correlations above 0.76. However, it was found that both products overestimate surface concentrations. MERRA-2 performed better, with approximately 30% lower bias than CAMS. Time series analysis showed that the study area is strongly impacted by emissions BB in the dry period, mainly in August and September. Furthermore, our findings indicate a positive trend in increasing PM 2.5 concentrations, with a notable rise observed since 2014. The average PM 2.5 levels frequently exceed the daily air quality guidelines established by the WHO in 2021. It has been estimated that the population of this region is exposed to concentrations above 15 μg.m -3 , on average, more than 30 days per year. Our results contribute to the evaluation of MERRA-2 and CAMS products for Amazon and provide a corrected estimate for surface PM 2.5 . Recent concerns about air quality and the implementation of new surface monitoring networks may improve the evaluation of reanalysis products. In the short term, the need for this information makes our assessments indispensable.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Atomistic simulations and machine learning of solute grain boundary segregation in Mg alloys at finite temperatures

Understanding solute segregation thermodynamics is the first step in investigating grain boundary (GB) properties, such as strong yttrium (Y) effects on grain growth and texture evolution in micro-scale polycrystalline magnesium (Mg) alloys. To estimate the average GB segregation behavior in low-solute-concentration Mg alloys (e.g., 2 at.% Y), a state-of-the-art spectral approach is applied based on a per-site segregation energy spectrum for Y solute atoms at zero K obtained from molecular statistics (MS) simulations of ~10 4 GB sites in Mg symmetric tilt GBs (STGBs). Although selected MS simulation results are consistent with verification by density functional theory (DFT) calculations, estimates of average segregation tendency based on the zero-K energy spectrum deviate from experimental observations. To resolve this problem, thermodynamic integration (TI) methods based on molecular dynamics (MD) simulations are used to determine the per-site segregation free energies of Y at representative GB sites, which show contributions beyond harmonic approximations can be important for certain GB sites at high temperatures. A surrogate model of per-site segregation free energy is constructed from a small set of TI data points using stacking cross-validation regressors and physics-informed descriptors. This model is applied to predict the Y segregation free energy spectra for thousands of GB sites in Mg STGBs with uncertainty quantification. Finally, the average segregation tendency predicted by the spectral approach based on the free energy spectra agrees well (within the uncertainty range) with experimental observations for micro-scale polycrystalline Mg alloys at typical thermomechanical processing temperatures (500 ~ 800 K), where thermodynamic equilibrium states are likely to be achieved due to fast diffusion.

Atomistic simulations↗
DOE OSTI2022

Photosynthesis phenology, as defined by solar-induced chlorophyll fluorescence, is overestimated by vegetation indices in the extratropical Northern Hemisphere

Vegetation phenology is highly sensitive to climate change, although the data and methods used to estimate key phenological states can influence this sensitivity. Because of its direct relation to leaf photosynthetic carbon uptake, remotely sensed solar-induced chlorophyll fluorescence (SIF) can provide new insight assessing changes in vegetation phenology. In this work, we investigated the potential of using a SIF time series product named contiguous SIF (CSIF) to estimate spring, summer, and autumn phenology in the extratropical Northern Hemisphere (>30°N) and compared the results with those based on Moderate Resolution Imaging Spectroradiometer (MODIS) Normalized Difference Vegetation Index (NDVI) for the period 2001–2018. Overall, we found similar spatial patterns in phenological states. However, specific dates of key phenological events differed when using CSIF vs. MODIS NDVI data. NDVI data indicated that the growing season started earlier (by 10.1 days on average) and ended later (11.5 days on average) relative to CSIF data. This implies that actual periods for photosynthetic activity are shorter (by 21.6 days on average) than those estimated from vegetation indices more directly related to changes in canopy structure. These large differences between results from NDVI and that from CSIF suggest that vegetation indices such as NDVI seem to overestimate the period for active photosynthesis over the extratropical Northern Hemisphere. Furthermore, while phenology of the early growing season is dominated by temperature for both NDVI and CSIF data, phenology of the late growing season is mainly controlled by temperature for NDVI but by precipitation for CSIF. Our findings were further confirmed by other SIF (GOME-2 SIF) and vegetation index (MODIS EVI) datasets. Phenology modes in Earth system modelling are often parameterized using leaf unfolding and senescence from either station or satellite observations. Our results imply that canopy structure-based parameterization schemes may have overestimated photosynthesis active period, and thus productivity responses. We conclude that SIF data offers a novel and unique approach for assessing phenological change - one that is more directly tied to the carbon cycle and how it is being influenced by climate change.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Improved natural convection heat transfer correlations for reactor cavity cooling systems of high-temperature gas-cooled reactors: From computational fluid dynamics to Pronghorn

The Reactor Cavity Cooling System (RCCS) is a common reactor safety system in High Temperature Gas Cooled Reactors (HTGR) that removes heat from the Reactor Pressure Vessel (RPV) by radiation ($\sim 80\%$) and natural convection ($\sim 20\%$). For simulation of accident scenarios of HTGRs, intermediate fidelity and system codes models must be employed for limiting the models' execution time. While accurate quantification of the radiative heat transfer is available in these models, quantification of natural convection must rely on correlations of questionable accuracy for the Nusselt number. Commonly used correlations are based in experiments performed at low Rayleigh numbers and/or using isothermal walls in simplified geometries. Here, this work improves on the accuracy of natural convection heat transfer correlations in support for HTGR designs. These correlations include both local and average Nusselt numbers as a function of the global Rayleigh number, the local Rayleigh number, and the temperature profile at the hot wall of the RCCS. In the absence of dedicated experiments and the difficulty of performing high-fidelity simulations at realistic Rayleigh numbers, the data to fit the correlations are generated with Computational Fluid Dynamics (CFD) using Reynolds Averaged Navier-Stokes (RANS) models. First, a careful selection of the RANS turbulence model is performed by comparing the results obtained with different RANS turbulence models against high fidelity simulations of natural convection at $Ra \ 1 \times 10^{11}$ in a rectangular cavity. Next, the selected model is used to perform simulations of an HTGR cavity at different high Rayleigh numbers $\in [6.1 \times 10^{11},2.9 \times 10^{13}]$ to encompass several HTGR designs, assuming an isothermal RPV wall. The results obtained are used to fit a correlation for the average and space-varying Nusselt number as a function of the global and local Rayleigh numbers via a sparsity-promoting least-squares method. The selected RANS model is then used to perform simulations of a PBMR 400 HTGR cavity with the temperature profiles at the RPV wall obtained during a PLOFC transient. We use the results obtained to fit a temperature-dependent correction to the space-varying Nusselt number with the sparsity-promoting least-squares method. The results obtained in this work, enable system-level codes, such as Pronghorn, to perform higher-fidelity simulations of the heat exchange process in the RCCS while still maintaining a low computational cost.

42 ENGINEERING↗
DOE OSTI2023

Multiphysics analysis of fuel Fragmentation, Relocation, and dispersal Susceptibility–Part 2: High-Burnup Steady-State operating and fuel performance conditions

The US nuclear industry is pursuing increased cycle lengths and increasing the peak rod-averaged burnup in an effort to increase the economic viability of the US nuclear fleet. Increasing burnup will afford economic viability by enabling utilities to optimize core designs to reduce the number of fresh fuel assemblies per cycle and allow nuclear power plants to operate for a longer period of time. Longer operating periods will also decrease the number of outages experienced by a nuclear power plants and, therefore, offer utilities significant operational savings. However, extending the peak rod-averaged burnup beyond 62 GWd/tU results in operating fuel rods to higher burnup under higher power conditions. This operating regime is expected to result in higher fuel temperatures, fission gas release (FGR), and rod internal pressures (RIPs) that may challenge historical safety basis and affect high-burnup (HBU) experimental testing. In particular, these conditions directly affect fuel fragmentation, relocation, and dispersal (FFRD) susceptibility, so understanding the pretransient operating conditions is critical for developing test plans that evaluate the FFRD and develop strategies to mitigate it. This paper evaluates the operating conditions and fuel performance of HBU (greater than62 GWd/tU rod average) fuel. Additionally, it investigates fuel performance sensitivities and discusses the effect on fuel performance. Here, this work used two codes. Virtual Environment for Reactor Applications (VERA) was used to calculate steady-state power histories, identify HBU operating conditions using 10 different realistic HBU core designs, and down-select rods to a representative subset of fuel rods for subsequent BISON evaluation. The BISON fuel performance code was used to investigate steady-state HBU operating conditions and assess uncertainties associated with FGR and its effect on fuel temperatures and RIPs. The VERA and BISON results will provide direct input for HBU experimental testing and support subsequent TRACE and BISON transient fuel performance analyses.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Dynamics of disordered mechanical systems with large connectivity, free probability theory, and quasi-Hermitian random matrices

Disordered mechanical systems with high connectivity represent a limit opposite to the more familiar case of disordered crystals. Individual ions in a crystal are subjected essentially to nearest-neighbor interactions. In contrast, the systems studied in this paper have all their degrees of freedom coupled to each other. Thus, the problem of linearized small oscillations of such systems involves two full positive-definite and non-commuting matrices, as opposed to the sparse matrices associated with disordered crystals. Consequently, the familiar methods for determining the averaged vibrational spectra of disordered crystals, introduced many years ago by Dyson and Schmidt, are inapplicable for highly connected disordered systems. In this paper we apply random matrix theory (RMT) to calculate the averaged vibrational spectra of such systems, in the limit of infinitely large system size. At the heart of our analysis lies a calculation of the average spectrum of the product of two positive definite random matrices by means of free probability theory techniques. We also show that this problem is intimately related with quasi-hermitian random matrix theory (QHRMT), which means that the ‘hamiltonian’ matrix is hermitian with respect to a non-trivial metric. This extends ordinary hermitian matrices, for which the metric is simply the unit matrix. The analytical results we obtain for the spectrum agree well with our numerical results. The latter also exhibit oscillations at the high-frequency band edge, which fit well the Airy kernel pattern. We also compute inverse participation ratios of the corresponding amplitude eigenvectors and demonstrate that they are all extended, in contrast with conventional disordered crystals. Finally, we compute the thermodynamic properties of the system from its spectrum of vibrations. In addition to matrix model analysis, we also study the vibrational spectra of various multi-segmented disordered pendula, as concrete realizations of highly connected mechanical systems. A universal feature of the density of vibration modes, common to both pendula and the matrix model, is that it tends to a non-zero constant at vanishing frequency.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Characteristics of upward-connecting-leader current leading to attachment in downward negative cloud-to-ground lightning strokes

For this work, we analyzed currents associated with upward connecting leaders (UCLs) initiated from the Kennedy Space Center Industrial Area Tower in two negative cloud-to-ground strokes that struck the tower. One stroke was also recorded using a high-speed video camera located 760 m from the KSC IAT. The NLDN-reported peak currents for the two strokes were – 31.7 and – 98.5 kA. During the UCL development phase the current waveforms exhibited a monotonically (quasi-exponentially) increasing “background” current overlaid with 10-μs scale pulses with a median amplitude of 51.1 A. The UCL current durations for the two strokes were 1039 and 449 μs, respectively. During the pre-attachment processes (UCL and slow front) the total negative charge effectively transferred to ground were 70.2 and 55 mC, respectively. For the stroke captured on high-speed video, the average line-charge-density for the 109-m long UCL was found to be 0.5 mC/m. The average UCL 2-D speed was 2.4 × 10 5 m/s, and it was observed to accelerate toward the downward leader prior to attachment. We observed that UCL-pulse amplitudes are larger, background currents are higher, and interpulse intervals are shorter at later times during UCLs, which can be attributed to the intensification of the local electric field due to the approaching downward negative leader. The median positive charge injected into the UCL by a pulse was 297 μC. The UCL associated with the higher peak-current stroke produced the highest injected pulse-charge values about three times sooner during its development, likely due to the 2–2.7 times faster average downward leader vertical speeds.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

The relation between lignin sequence and its 3D structure

Background: Lignin, the second most abundant biopolymer on earth, plays a major structural role in plants, conferring mechanical strength and regulating water conduction. Understanding the three-dimensional structure of lignin is important for fundamental reasons as well as engineering plants towards lignin valorization. Lignin lacks a specific primary sequence, making its average chemical composition the focus of most recent studies. However, it remains unclear whether the 3D structure of lignin molecules depends on their sequence. Methods: In this work, we performed all-atom molecular dynamics simulation of three S/G-lignin molecules with the same average composition but different sequence. Results: A detailed statistical analysis of the radius of gyration and relative shape anisotropy reveals that the lignin sequence has no statistically significant effect on the global three-dimensional structure. We found however, that homopolymers of C-lignin with the same molecular weight have smaller radii of gyration than S/G-lignin. We attribute this to lower hydroxyl content of C-lignin, which makes it more compact and rigid. Conclusions: The 3D structure of lignin is influenced by the overall content of monomeric units and interunit linkages and not by its precise primary sequence. General Significance: Lignin is assumed to not have a well-defined primary structure. The results presented here demonstrate there are no significant differences in the global 3D structure of lignin molecules with the same average composition but different primary sequence.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Assessing the use of portable air cleaners for reducing exposure to airborne diseases in a conference room with thermal stratification

The COVID-19 pandemic has highlighted the need for strategies that mitigate the risk of aerosol disease transmission in indoor environments with different ventilation strategies. It is necessary for building operators to be able to estimate and compare the relative impacts of different mitigation strategies to determine suitable strategies for a particular situation. Using a validated CFD model, this study simulates the dispersion of exhaled contaminants in a thermally stratified conference room with overhead heating. The impacts of portable air-cleaners (PACs) on the room airflow and contaminant distribution were evaluated for different PAC locations and flow rates, as well as for different room setups (socially distanced or fully occupied). To obtain a holistic view of a strategy's impacts under different release scenarios, we simultaneously model the steady-state distribution of aerosolized virus contaminants from eight distinct sources in 18 cases for a total of 144 release scenarios. The simulations show that the location of the source, the PAC settings, and the room set-up can impact the average exposure and PAC effectiveness. For this studied case, the PACs reduced the room average exposure by 31%-66% relative to the baseline case. Some occupant locations were shown to have a higher-than-average exposure, particularly those seated near the airflow outlet, and occupants closest to sources tended to see the highest exposure from said source. We found that these PACs were effective at reducing the stratification caused by overhead heating, and also identified at least one sub-optimal location for placing a PAC in this space.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Investigation of HVAC operation strategies for office buildings during COVID-19 pandemic

To minimize the indoor transmission of contaminants, such as the virus that can lead to COVID-19, buildings must provide the best indoor air quality possible. Improving indoor air quality can be achieved through the building's HVAC system to decrease any concentration of indoor contaminants by dilution and/or by source removal. However, doing so has practical downsides on the HVAC operation that are not always quantified in the literature. This paper develops a temporal simulation capability that is used to investigate the indoor virus concentration and operational cost of an HVAC system for two mitigation strategies: (1) supplying 100% outdoor air into the building and (2) using different HVAC filters, including MERV 10, MERV 13, and HEPA filters. These strategies are applied to a hypothetical medium office building consisting of five occupied zones and located in a cold and dry climate. We modeled the building using the Modelica Buildings library and developed new models for HVAC filtration and virus transmission to evaluate COVID-19 scenarios. We show that the ASHRAE-recommended MERV 13 filtration reduces the average virus concentration by about 10% when compared to MERV 10 filtration, with an increase in site energy consumption of about 3%. In contrast, the use of 100% outdoor air reduces the average indoor concentration by about an additional 1% compared to MERV 13 filtration, but significantly increases heating energy consumption. Use of HEPA filtration increases the average indoor concentration and energy consumption compared to MERV 13 filtration due to the high resistance of the HEPA filter.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Excessive radon-based radiation in indoor air caused by soil building materials in traditional homes on Đồng Văn karst plateau, northern Vietnam

Radon-based radiation from natural soil building materials is an important factor likely influencing residents’ health as a contributing source of natural radiation. This work aims to quantify the nuclide-specific α-radiation of isotopes 222 Rn and 220 Rn in common types of houses in a region of northern Vietnam, Ɖông Văn karst plateau, to preliminarily (i) evaluate the total annual effective dose rates and (ii) assess the relative risk of cancer induction from indoor α-radiation for inhabitants. The average 222 Rn concentrations in all house types were lower than 100 Bq m -3 , but 220 Rn abundances were far higher than 222 Rn, even up to >1000 Bq m -3 in air close to a wall of unfired-soil bricks. The estimated total annual effective dose rates from indoor 222 Rn and 220 Rn and their progenies to residents with daily exposure of 13 h in the various types of houses range from 3.1 to 4.3 mSv a -1 for houses constructed with modified materials, but up to higher than 6 mSv a -1 in houses with raw building materials. The average risk of developing lung cancer as a consequence of a lifetime exposure to indoor α-radiation in affected homes ranges from 3.9% to 14.6%. 220 Rn and its metallic progenies contribute more than 80% of the total average lung cancer risk from total radon, being responsible for a range of 2.7–14.6% of the risk of developing lung cancer.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Integration and validation of some modules for modelling of high-speed chemically reactive flows in two-phase gas-droplet mixtures

Three modules are integrated into the built-in OpenFOAM rhoCentralFoam solver towards accurate and efficient modelling of high-speed chemically reactive flows in two-phase gas-droplet mixtures within the OpenFOAM 10.0 framework. The first module is the mixture-averaged diffusion model. The second module is the built-in OpenFOAM Lagrangian solver coupled with optimised droplet drag coefficient and convective heat transfer coefficient sub-models. The last module is a sparse stiff chemistry solver based on dynamic adaptive hybrid integration (AHI-S). The optimised droplet sub-models are first verified in correct implementation for subsequent simulations in this work. Further, they show good accuracy against experimental and analytical data in the modelling of ammonia droplet acceleration and cooling in the flowing and/or low-temperature air. The accuracy and efficiency gains related to the mixture-averaged diffusion model and the AHI-S chemistry solver are examined by simulating 1-D detonation propagation in ammonia droplet-free/laden ammoniaoxygen mixtures. Numerical results of detonation propagation speed, gaseous temperature, density, and species distributions around the induction zone show good agreement with experimental data and analytical solutions. Compared to the built-in OpenFOAM diffusion model, the mixture-averaged diffusion model provides different numerical predictions of pulsating instabilities in detonation propagation. It shows better accuracy in depicting the detonation structure within the droplet-free section attributed to improved multi-component diffusion modelling. Compared to the built-in OpenFOAM solver EulerImplicit (backward Euler), the AHI-S chemistry solver reduces the computational cost by around 50%. It achieves satisfactory accuracy in calculating detonation propagation speed within the droplet-free section with the optimal efficiency when the safety factor, β, equals 0.5.

42 ENGINEERING↗
DOE OSTI2025

Comparison of interlaminar damage modeling strategies for hybrid composite/aluminum laminates subjected to low-velocity impact

Low-velocity impact of hybrid metal-composite structures was investigated experimentally and computationally. Composite laminates consisting of 2D woven glass fiber reinforced polymer (GFRP) and carbon fiber reinforced polymer (CFRP) were joined with a 6061-T6 aluminum plate using an epoxy adhesive. Two variations of the structure were studied; one consisting of all plies oriented at 0° and one consisting of all plies oriented at 45°. A drop tower was used to impact structures at a range of energies, including energies above and below the threshold at which the aluminum layer was perforated. Numerical simulations were implemented using Sierra/SM, an in-house transient dynamics finite element code developed at Sandia National Laboratories. A Hosford plasticity model was used to describe the response of the aluminum layer. A newly implemented orthotropic continuum damage mechanics (CDM) constitutive model was used to represent the composite laminate. This 3D-CDM model was compared to a cohesive zone model (2D-CDM/CZM) to investigate efficacy of aluminum perforation energy prediction, delamination prediction, and computational cost. Accuracy of each model was evaluated using the experimental results. Each showed good agreement with the tests for both the force and velocity histories, as well as the observed damage mechanisms. The 2D-CDM/CZM model was marginally more accurate in capturing both the composite and aluminum behavior — this model averaged error percentages of -11.2% and 10.8% for residual velocity and peak force, respectively. Meanwhile, the 3D-CDM model predictions yielded average error percentages of -35.5% (velocity) and 22.6% (force). However, the 3D-CDM model generally resulted in a decreased computational cost; the average run time was 14% shorter than the 2D-CDM/CZM model and 3x as many timesteps per hour were computed using the same computational resources. In conclusion, new experimental data on the impact and perforation resistance of metal-composite laminates is presented in addition to numerical predictions of the impact behavior.

Carbon fiber↗
DOE OSTI2025

HydroEcoLSTM: A Python package with graphical user interface for hydro-ecological modeling with long short-term memory neural network

Machine learning (ML) is emerging as a promising tool for modeling hydro-ecological processes due to the increasing availability of large environmental data. However, the use of ML requires sufficient programming knowledge due to a lack of a graphical user interface (GUI). In this study, we introduced a GUI package, named HydroEcoLSTM, with the long short-term memory network (LSTM) as the core model, that allows non-ML experts to utilize their domain knowledge to construct complex ML models. We demonstrated the functionalities of HydroEcoLSTM with two practical examples, including (1) predictions of streamflow in both gauged and ungauged catchments and (2) predictions of multiple outputs (i.e., streamflow and isotope transport from two catchments). The simulation results obtained in both case experiments are satisfactory. In the first example, the average Nash–Sutcliffe Efficiency (NSE) for streamflow simulation during the testing period is 0.79 while the application of the trained model in two assumed ungauged catchments also achieves the average NSE of 0.68. In the second example, the average NSE for streamflow and instream isotope simulation during the testing period is 0.71. Ultimately, applications of HydroEcoLSTM with real-world examples demonstrate its potential use for practical applications and research without requiring extensive coding skills.

54 ENVIRONMENTAL SCIENCES↗