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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 433 records · Page 24
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Heterogeneous energetic material damage simulator (HEDS): A deep learning approach to simulate damage–sensitivity linkages

Damage in the microstructures of energetic materials (EMs), such as propellants and plastic bonded explosives (PBXs), can significantly alter their response to external loads. Both sensitization and desensitization can occur, causing concerns with safety and performance in the field; predictive models that connect damage and the sensitivity of EMs can enable design and provide confidence in their robustness and reliability. However, modeling of damage evolution is challenging for real microstructures of EMs; samples of damaged EMs are difficult to obtain, thereby hindering experiments and direct numerical simulations to determine the sensitivity of EMs at various stages of damage. Here, we develop an approach to generate synthetic, i.e., in silico produced, damaged microstructures for use in simulations to connect damage levels to sensitivity. The development of the present workflow to generate and impose varying levels of damage in microstructures, known as HEDS (Heterogeneous Energetic Material Damage Simulator), begins with a small set of images of damaged PBXs and combines a collection of deep neural network techniques to generate microstructures with varying levels of damage. By making the synthetic microstructures conform closely to those observed in available real, imaged microstructures, we develop an ensemble of damaged microstructures that can be used for in silico shock experiments. HEDS develops these microstructure ensembles as level set fields, which are directly employed in a sharp interface Eulerian hydrocode where shock simulations are performed to quantify the energy release rate from hotspot fields generated in the microstructure. These capabilities can be useful for the analysis and assessment of changes in the sensitivity of EMs and to design formulations that are less susceptible to damage-induced changes in sensitivity and performance.

Fang, Irene (ORCID:0009000844557122)↗
DOE OSTI2024

Decomprolute is a benchmarking platform designed for multiomics-based tumor deconvolution

Tumor deconvolution is a reliable way to disentangle the diverse cell types that comprise solid tumors. To date, however, both the algorithms developed to deconvolve tumor samples, and the gold standard datasets used to assess the algorithms are geared toward the analysis of gene expression (e.g., RNA-seq) rather than protein levels in tumor cells. While gene expression is less expensive to measure, protein levels provide a more accurate view of immune markers. To facilitate the development as well as improve the reproducibility and reusability of multi-omic deconvolution algorithms, we introduce Decomprolute, a Common Workflow Language framework that leverages containerization to compare tumor deconvolution algorithms across multiomic data sets. Decomprolute incorporates the large-scale multiomic data sets produced by the Clinical Proteomic Tumor Analysis Consortium (CPTAC), which include matched mRNA expression and proteomic data from thousands of tumors across multiple cancer types to build a fully open-source, containerized proteogenomic tumor deconvolution benchmarking platform. The platform consists of modular architecture and it comes with well-defined input and output formats at each module. As a result, it is robust and extendable easily with additional algorithms or analyses. The platform is available for access and use at http://pnnl-compbio.github.io/decomprolute.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Coolant Channel Design for Additively Manufactured Reactor Cores

Additive manufacturing (AM) methods are currently being explored for applications in nuclear reactors to make advanced reactors more efficient, safe, and reliable. The Transformational Challenge Reactor (TCR) program has explored AM for nuclear by designing a high-temperature gas reactor (HTGR) using an AM silicon carbide fuel form with uranium nitride–tristructural isotropic fuel. In this study, we detail the design process for the TCR fuel form’s coolant channels using computational fluid dynamics models with conjugate heat transfer. Additionally, this work discusses how these models were interfaced with other design teams, project milestones, and the agile design method used to mature the reactor design. The methodology deployed was able to create a channel design with lower maximum fuel temperatures and thermal stresses in the fuel form over traditional channel designs that can be manufactured subtractively. These results were achieved with only small manufacturing penalties. Results are discussed and presented on lessons learned for designing AM components for nuclear reactors. Finally, areas of opportunity are discussed for advanced design tools to further automate design activities and optimize reactors with fewer built-in assumptions.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2022

Modeling Framework to Analyze Performance and Structural Reliability of Solid Oxide Electrolysis Cells

Solid oxide electrolysis cells (SOEC) have been receiving significant attention recently because of their high energy efficiency and fast hydrogen production. In this study a multi-physics model to simulate the SOEC performance and structural reliability of a state-of-the-art planar SOEC design was developed. The electrochemical reactions, fluid dynamics, species transport, electron transfer, and heat transfer were modeled in the commercial computational fluid dynamics (CFD) software STAR-CCM+. The thermomechanical analysis and the associated structural reliability evaluations were conducted using the commercial finite element analysis software ANSYS. The electrochemistry model was validated by using the experimentally obtained current-voltage (I-V) characteristics of the electrode-supported SOECs. The reliability analysis using a risk-of-rupture approach showed low failure probabilities under standard operating conditions considered in this study. For cells operated at voltages well above a thermoneutral voltage, the reliability evaluations indicated a potential risk of cell failure, but the damage was concentrated locally in specific areas of the cell which typically do not lead to total loss of cell function. The presented approach provides insights for evaluating representative cell and stack performances and structural reliability without intensive testing and for developing optimally performing and structurally reliable SOECs for efficient hydrogen generation.

25 ENERGY STORAGE↗
DOE OSTI2025

Experience of developing highly reliable Tuner components (piezo actuators and cold stepper motor actuators) for SRF Linac

The resonance control team at FNAL has led the design of the LCLS-II SRF Linac SRF cavity tuner subsystem. The Linac is expected to operate for over 30 years, and the longevity of the tuner is crucial to the overall reliability of the Linac. When the tuner's design was started, there were no active actuators (stepper and piezo) that could meet the longevity requirements of the Linac. The FNAL resonance control team, in collaboration with industrial partners (Phytron and PI), has developed actuators that have been shown to withstand a cryogenic and insulating vacuum environment for over 100 years in accelerated lifetime tests. Details of actuators design and longevity testing will be presented. Now, practically all (small and large) SRF systems that are under construction around the world are using actuators developed at FNAL. A review of possible actuators improvement will be presented.

Pischalnikov, Yuriy [Fermilab]↗
DOE OSTI2022

Application of Manufacturing Quality Management Principles to PV System Installations

To help SETO/DOE achieve its goals, the IBTS team proposed a project addressing system reliability by improving installation standards and quality management. The proposed approach was designed to help achieve measurable reductions in installation defect density and improvements in the performance of PV systems by optimizing design and installation of residential and commercial PV systems. This approach addressed the soft costs associated with installations and quality management. The project demonstrated improved system reliability and reduced PV system installation costs. The software developed improved operations, decreased risk, and increased the overall value of PV systems across their lifecycle. The project used several data collection methods, including extensive industry surveys, face-to-face high-level interviews at industry conferences, stakeholder teleconferences, and in-depth interviews conducted by IBTS staff. Results from the research found the industry needs a uniform assessment method for national providers to be more efficient; the software should support both code officials and installers; most industry stakeholders would find value in a centralized software system that allows them to collect, report, and review information on in-process and completed solar installations; and mobile solutions that bridge existing knowledge gaps with inspectors and integrate with existing methodologies (such as permitting software) are of great value. The software solution developed is web-based, allowing for national access, and is built on a Google Firebase platform that can handle significant users and data. It can be used onsite or remotely, allowing for code compliance to continue despite ongoing pandemic related delays or shutdowns for local economies. The information provided by the software tool allows users to uniformly assess a system for compliance and use that aggregated data to identify training topics or create internal process designed to improving issues and reducing occurrence. This solution has multiple benefits in managing quality at time of use and promoting an increase in future safety and quality through education. Perhaps most importantly, this software increases public safety by ensuring compliance of installed systems and allows for local AHJs to remotely engage specialized and qualified solar specific expertise for oversite of the installation in their jurisdictions. Data analysis provides the quality feedback loop identifying the root cause of failure and drives installation practices to improve through training and education, resulting in systems with higher performance, greater reliability, and reduced operations and maintenance costs. With the successful completion of this project, the industry can expect reduced soft costs and increased performance and safety and will ultimately benefit from longer performing systems that cost less to operate.

14 SOLAR ENERGY↗
DOE OSTI2022

High-Entropy and Superstructure-Stabilized Layered Oxide Cathodes for Sodium-Ion Batteries

Layered transition metal oxides are appealing cathodes for sodium-ion batteries due to their overall advantages in energy density and cost. But their stabilities are usually compromised by the complicated phase transition and the oxygen redox, particularly when operating at high voltages, leading to poor structural stability and substantial capacity loss. Here, in this study, an integrated strategy combing the high-entropy design with the superlattice-stabilization to extend the cycle life and enhance the rate capability of layered cathodes is reported. It is shown that the as-prepared high-entropy Na 2/3 Li 1/6 Fe 1/6 Co 1/6 Ni 1/6 Mn 1/3 O 2 cathode enables a superlattice structure with Li/transition metal ordering and delivers excellent electrochemical performance that is not affected by the presence of phase transition and oxygen redox. It achieves a high reversible capacity (171.2 mAh g –1 at 0.1 C), a high energy density (531 Wh kg –1 ), extended cycling stability (89.3% capacity retention at 1 C for 90 cycles and 63.7% capacity retention at 5 C after 300 cycles), and excellent fast-charging capability (78 mAh g –1 at 10 C). This strategy would inspire more rational designs that can be leveraged to improve the reliability of layered cathodes for secondary-ion batteries.

25 ENERGY STORAGE↗
DOE OSTI2023

Active Lithium Injection for a Real Time Control of the Divertor Heat Flux for Fusion Devices

When the local heat flux exceeds specified flux limit, tungsten PFC surfaces can be damaged, which is not acceptable for a reliable reactor operations. The divertor PFCs are typically designed for a specific heat flux limit usually assuming an average steady-state heat flux which is typically 5–10 MW/m 2 . However, in addition to steady-state heat flux, fusion reactor divertor PFCs could experience transient heat fluxes such as ELMs and/or other magnetic reconnection events which can deposit large transient heat fluxes onto the divertor PFCs. The transient divertor heat flux could be significantly larger than the steady-state heat flux which could damage the solid PFC surfaces. The divertor heat flux can be subjected to additional complications such as the uncertainties in the the divertor strike point heat flux projection. Moreover, there are additional experimental observations of non-axisymmetric power flux which can occur under non-axisymmetric magnetic perturbations. The liquid lithium (LL) PFCs is more resilient against such transient heat fluxes as they could evaporate LL as needed and the lost LL can be then replenished afterward. In this paper, we analyze a case for a transient divertor heat pulse of 1 MJ in 10 ms for a ITER-size reactor. This is a small perturbation (~ 0.1%) to the expected plasma stored energy compared to the previously analyzed case of 20 MJ heat pulse. Even with this relatively modest heat pulse, the LL surface undergoes ~ 100 °C temperature rise. However, the resulting LL surface heating without rapid cooldown mechanism could lead to excessive LL evaporation continuing well after the transient heat flux resulting in a significant Li injection of ~ 0.6 mol in about a 200 ms period. This amount of Li injection could cause plasma dilution and performance degradation. On the other hand, an active Li injection capability if optimized could prevent the LL surface temperature rise and thus reducing subsequent Li evaporation into the plasma by a factor of 7 compared to the passive LL PFC case. A crucial tool of active Li injection is a rapid response pellet injector which could inject light impurity pellets before the excessive heat flux could reach the divertor plate causing serious damage. A simple pellet ablation model suggests a favorable pellet deposition profile for smaller ~ 0.1 mm radius pellet with ~ 10–20 m/s velocity. Moreover, if it is possible to inject from the private flux region, the pellet injection efficiency into the high heat flux strike point region can be as high as 80% compared to ~ 50% for the injection from outer radius region. The pellet deposition efficiency can be further improved by designing a shell-pellet which can burst when a certain ablation fraction is reached. Finally, a possible implementation technique using an inductive pellet injector with a rapid time response of a few msec is proposed here which can be tested in NSTX-U.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Resilience and economics of microgrids with PV, battery storage, and networked diesel generators

Current designs and assessments of microgrids have ignored component reliability, leading to significant errors in predicting a microgrid’s performance while islanded. Existing life cycle cost studies on hybrid microgrids—which combine photovoltaics (PV), battery storage and networked emergency diesel generators—also have not identified all the potential economic opportunities. Reducing the number of emergency diesel generators through reliance on PV and battery, retail bill savings, and demand response and wholesale market revenue streams are all important. This paper provides a new statistical methodology that calculates the impact of distributed energy reliability and variability on a microgrid’s performance and a novel use of the optimization platform REopt to explore multiple cost savings and revenue streams. We examine the impacts for microgrids in California, Maryland, and New Mexico and show that a hybrid microgrid is a more resilient and cost-effective solution than a diesel-only system. Under realistic conditions, a hybrid microgrid can provide higher system reliability when islanded and have a lower life cycle cost under multiple market conditions than a traditional diesel generator-based system. The improved performance of the hybrid system is resilient to conditions experienced over the last 20 years in solar irradiance and sees little degradation in performance immediately after a hurricane. The cost savings to provide this more resilient backup power system as compared to a diesel-only microgrid are significant. The net present cost for a hybrid microgrid is 19% lower in New Mexico and 35% lower in Maryland than a diesel-only microgrid. In California, the net present cost of the hybrid microgrid is negative because, unlike a diesel-only microgrid, a hybrid microgrid has lower life cycle costs than the power costs without a microgrid.

25 ENERGY STORAGE↗
DOE OSTI2022

Planning, design and logistics of a decision analysis study: The FBI/Ames study involving forensic firearms examiners

This paper describes design and logistical aspects of a decision analysis study to assess the performance of qualified firearms examiners working in accredited laboratories in the United States in terms of accuracy (error rate), repeatability, and reproducibility of decisions involving comparisons of fired bullets and cartridge cases. The purpose of the study was to validate current practice of the forensic discipline of firearms/toolmarks (F/T) examination. It elicited error rate data by counting the number of false positive and false negative conclusions. Preceded by the experimental design, decisions, and logistics described herein, testing was ultimately administered 173 qualified, practicing F/T examiners in public and private crime laboratories. The first round of testing evaluated accuracy, while two subsequent rounds evaluated repeatability and reproducibility of examiner conclusions. This project expands on previous studies by involving many F/T examiners in challenging comparisons and by executing the study in the recommended double-blind format.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2021

Investigation of neutron noise in a micro-scale, natural circulation molten salt fission battery system

The Molten Salt Reactor (MSR) concept is a rapidly evolving Generation IV design that has recently attracted favorable attention due to the potential for reducing waste generation, realizing passive safety features, and seizing on the opportunity for cost effective economics. A specific novel micro-MSR, natural circulation, battery design concept involves placing all primary components within a single reactor vessel containment without the need of primary forced pumping. This small modular, integral design presents potential cost savings while producing safety, reliable, and transportable carbon-free power for decades. This investigation evaluates the neutron noise induced by density and flow fluctuations in a natural circulation MSR battery concept being developed at the University of Idaho. This study finds numerical solutions to the one-dimensional, one-group, coupled diffusion equations for a bare, homogeneous core, and evaluates neutron flux and delayed neutron precursor concentration noise due to core flow and fuel salt density perturbation sources. Noise analysis shows both point kinetic and space-dependent behavior is present despite the small size, low-flow, closely-coupled nature of the natural circulation MSR concept. Analysis shows that the low flow of the convective system results in noise behavior typically representative of a larger forced-circulation MSR system. Finally, noise techniques may also be useful in MSR core diagnostics as a non-invasive, low-cost radiological option to traditional monitoring schemes.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

Classification and computation of extreme events in turbulent combustion

In the design of practical combustion systems, ensuring safety and reliability is an important requirement. For instance, reliably avoiding lean blowout, flame flashback or inlet unstart is critical for ensuring safe operation. Currently, the science of predicting such events is based on prior experience, limited modeling or diagnostic tools and purely statistical approaches. Even though computational and experimental tools for studying combustion devices have vastly advanced in the last three decades, the analysis of such failure events has not been pursued widely. While the use of data for model development and calibration is being widely accepted, the extension to failure events introduces numerous challenges. In particular, the focus here is on so-called data-poor problems, where the cost of generating data is extremely high and is not easily amenable to existing computational and experimental approaches. Data-poor problems are particularly relevant when related to extreme events (also called anomalous events) that can lead to catastrophic failure of the system. It is argued that transient events that describe such failure can have different causal mechanisms. To develop the scientific inference process, a classification of such problems is used to determine specific modeling paths as well as computational tools needed. Research opportunities in the emerging field of extreme event prediction are highlighted in order to identify critical and immediate needs.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Accurate Prediction of pKb in Amines: Validation of the CAM-B3LYP/6-311+G(d,p)/SMD Model

Amines play several key roles in chemistry and biology and are involved in numerous industrial processes, often with significant economic impacts. Recently, amines are also garnering interest as catalysts for polymer synthesis and for CO 2 fixation, incentivizing the need to rapidly design and screen new amino compounds. Hence, developing reliable methods to predict their physicochemical properties, e.g., the base dissociation constant (pKb), is pivotal. Here, a density functional theory (DFT)-based approach was employed to compute the pKb of substituted amines, exploring the impact of several key parameters, including (i) the number of explicit water molecules at the reaction center, (ii) the van der Waals (vdW) surface, and (iii) solvent polarizability. In previous work, it was determined that including two explicit water molecules at the reaction center resulted in highly accurate pKb estimates for primary amines. Here, we find that including a third water molecule at the reaction center is essential for accurate pKb for secondary and tertiary amines. The revised methodology was then applied to a wider selection of amines, obtaining a minimum average error (MAE) < 0.4. In conclusion, this result represents an extension of our “easy-to-use method,” a simple and direct DFT approach exploiting CAM-B3LYP/SMD/6-311G+(d,p) to compute pKb without post facto modifications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Challenges and Possible Solutions in Aeroelastic Modeling for the Distributed Wind Industry

Aeroelastic modeling (AM) is the primary methodology for structural and performance assessment of any wind turbine; it provides an understanding of the impact of design parameters on turbine loading and power response before witnessing it in the field. Despite these advantages, the use of AM in the distributed wind technology (DWT) sector is limited. This article represents a short summary of an in-depth assessment by the authors of the status of AM and its role within the distributed wind technology design standards. The research gathered input and feedback from a large number of U.S. and international stakeholders, reviewed technical strengths and weaknesses of the current edition of the design standards, analyzed the minutes from recent industry workshops and meetings, collected publicly available AM templates, and provided an evaluation of the existing AM codes. Several goals were achieved including providing strategies for the load assessment categorization of turbines based on rotor swept area and archetype, and guidance for AM verification and validation. Recommendations within this study will advance the value and the ease-of-use of AM, thereby allowing the industry to better capitalize this underutilized tool, resulting in a more efficient design process, an easier path to certification, and overall better and more reliable distributed wind technology products.

17 WIND ENERGY↗
DOE OSTI2024

Multi-scale impacts of climate change on hydropower for long-term water-energy planning in the contiguous United States

Climate change impacts on watersheds can potentially exacerbate water scarcity issues where water serves multiple purposes including hydropower. The long-term management of water and energy resources is still mostly approached in a siloed manner at different basins or watersheds, failing to consider the potential impacts that may concurrently affect many regions at once. There is a need for a large-scale hydropower modeling framework that can examine climate impacts across adjoining river basins and balancing authorities (BAs) and provide a periodic assessment at regional to national scales. Expanding from our prior assessment only for the United States (US) federal hydropower plants, we enhance and extend two regional hydropower models to cover over 85% of the total hydropower nameplate capacity and present the first contiguous US-wide assessment of future hydropower production under Coupled Model Intercomparison Project phase 6’s high-end Shared Socioeconomic Pathway 5-8.5 emission scenario using an uncertainty-aware multi-model ensemble approach. We present regional hydropower projections, using both BA regions and US Hydrologic Subregions (HUC4s), to consistently inform the energy and water communities for two future periods—the near-term (2020–2039) and the mid-term (2040–2059) relative to a historical baseline period (1980–2019). We find that the median projected changes in annual hydropower generation are typically positive—approximately 5% in the near-term, and 10% in the mid-term. However, since the risk of regional droughts is also projected to increase, future planning cannot overly rely on the ensemble median, as the potential of severe hydropower reductions could be overlooked. The assessment offers an ensemble of future hydropower generation projections, providing regional utilities and power system operators with consistent data to develop drought scenarios, design long duration storage and evaluate energy infrastructure reliability under intensified inter-annual and seasonal variability.

13 HYDRO ENERGY↗
DOE OSTI2024

Device Feasibility Analysis of Multi-level FeFETs for Neuromorphic Computing

As an emerging non-volatile memory device technology, Ferroelectric Field-Effect Transistors (FeFETs) can enable low-power, adaptive intelligent system design. However, device dimension and operating voltage dependent reliability issues of scaled FeFETs can ultimately lead to degraded performance in solving machine learning tasks. In this article, detailed experimental characterization of FeFET devices of different dimensions have been carried out to explicitly evaluate the non-ideal behavior in device conductance programming properties like number of programming states, cycle-to-cycle (C2C) variations, device-to-device (D2D) variations, and state retention. A hardware-aware software simulation approach has been adopted to capture the adversarial effects of the non-idealities on recognition accuracy through algorithm-level performance assessment by including them in NeuroSim, a popular neural network hardware simulator, to execute a neural network model considering all other hardware constraints. With the added non-idealities, significant accuracy degradation has been observed compared to the ideal scenarios where D2D variations play the most critical role. Thereafter, feasibility of a variation-aware training method has been evaluated to tackle the accuracy drop.

42 ENGINEERING↗
DOE OSTI2023

Multifold Insights for Power System Dynamics From Data Assimilation: Meeting Current Challenges

The world’s electric power grids have evolved over the last 120 years from a single power line to today’s large networks. The evolution will continue at an accelerated rate with extensive smart grid development worldwide. Here for example, the U.S. government has set a goal of reaching 100 percent carbon pollution-free electricity by 2035, while the Department of Energy (DOE) shared a goal to deploy 30 GW and 110 GW of offshore wind by 2030 and 2050, respectively. To meet such ambitious goals, in the years to come, a significant percentage of electricity will come from intermittent renewable sources, electric vehicles (EVs), and be supplied to a vast number of loads that will actively respond to grid conditions and incentive signals. This development is largely driven by environmental and economic factors, such as reducing carbon emissions and saving electricity cost for consumers. These energy resources lead to new uncertain behaviors and dynamics which the grid has never seen and were not considered in its design. Operating such a dynamic grid with sufficient reliability and efficiency is a monumental challenge.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Estimating epistemic uncertainty in soil parameters for nonlinear site response analyses: Introducing the Latin Hypercube Sampling technique

This study quantifies the effects of epistemic uncertainty in soil parameters on nonlinear (NL) site response analysis (SRA) results, validated against the data recorded at a well-instrumented geotechnical downhole array located in Japan. To this end, a one-dimensional soil column model of the Service Hall Array (SHA) near the Kashiwazaki-Kariwa Nuclear Power Plant (KKNPP) is developed using the finite element (FE) program LS-DYNA. The dynamic stress–strain relationship is characterized by a modified two-stage hyperbolic (MTH) NL backbone curve formulation capable of capturing soil behavior at both small- and large-shear strains. The model is then validated against the ground motion recordings to capture the model bias. The uncertainties associated with the shear-wave velocity profile (a small-strain soil property) and soil shear strength (a large-strain soil property) are incorporated in NL SRA to quantify their separate and joint randomization effects on the results. This study proposes using the Latin Hypercube Sampling (LHS) method as an efficient alternative to commonly used methods, such as Standard Monte Carlo (SMC), to account for uncertainty propagation in such reliability analysis. Both low-intensity and design-level records from the recordings at the SHA are applied to study the contribution of the small- and large-strain NL dynamic soil properties. Results from 46,200 NL FE analyses (23,100 per input motion) are presented. Measured and predicted site response, using recorded ground motions at this downhole array, is compared to assess the significance of soil parameter uncertainty on the observed ground motion dispersions. It is demonstrated that increasing the number of soft realizations and implementing higher level earthquake intensity lead to higher ground motion dispersion. Unlike past studies in randomization of Vs profiles with the SMC method, the LHS method is shown to have no significant effect on the predicted median surface response spectra and amplification factors (AFs) for this case study.

Engineering↗