Data for "In-Situ Relative Calibration of Bragg Crystals with Monte Carlo Line Ratio Analysis"
Explore the source record for details and available documents.
Kraus, B. Frances↗
SEARCH · Search NASA
Results for “calibration data”
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.
Bayesian calibration of strength model parameters from Taylor impact data
Materials strength plays a key role in determining the mechanical response of engineered structures. As such, accurate strength models are crucial in simulations involving complex loading conditions, particularly when deformation in the plastic regime is deemed important. In this work, a Gaussian process based surrogate for a finite element simulation of a Taylor impact test is developed and used for Bayesian calibration of the Preston–Tonks–Wallace strength model. Here, the surrogate model is shown to closely approximate the salient features of the Taylor cylinder deformation and is validated against simulation output before being used in the strength model calibration routine. The results show that Taylor impact test data can be used in the calibration of constitutive equations through the use of a combination of data science techniques, namely Gaussian processes and Bayesian inference.
36 MATERIALS SCIENCE↗
In-orbit performance of the soft X-ray imaging telescope Xtend aboard XRISM
Here, we present a summary of the in-orbit performance of the soft X-ray imaging telescope Xtend onboard the X-Ray Imaging and Spectroscopy Mission (XRISM), based on in-flight observation data, including first-light celestial objects, calibration sources, and results from the cross-calibration campaign with other currently operating X-ray observatories. XRISM/Xtend has a large field of view of ${38{^{\prime }_{.}}5}$ $\times$ ${38{^{\prime }_{.}}5}$, covering an energy range of 0.4–13 keV, as demonstrated by the first-light observation of the galaxy cluster Abell 2319. It also features an energy resolution of 170–180 eV at 6 keV, which meets the mission requirement and enables us to resolve He-like and H-like Fe K$\alpha$ lines. Throughout the observation during the performance verification phase, we confirm that two issues identified in the Soft X-ray Imager (SXI) onboard the previous Hitomi mission—light leakage and crosstalk events—are addressed and suppressed in the case of Xtend. A joint cross-calibration observation of the bright quasar 3C 273 results in an effective area measured to be $\sim$420 cm$^{2}$ at1.5 keV and $\sim$310 cm$^{2}$ at 6.0 keV, which matches values obtained in ground tests. We also continuously monitor the health of Xtend by analyzing overclocking data, calibration source spectra, and day-Earth observations; the readout noise is stable and low, and contamination is negligible even one year after launch. A low background level compared with other major X-ray instruments onboard satellites, combined with the largest grasp ($\Omega _{\rm eff}\sim 60$ cm$^2$ deg$^2$) of Xtend, will not only support Resolve analysis, but also enable significant scientific results on its own. This includes near-future follow-up observations and transient searches in the context of time-domain and multi-messenger astrophysics.
instrumentation: detectors: Xtend↗
Constitutive Model Development for Aging Polymer Encapsulants (ASC P&EM FY2021 L2 Milestone 7836)
This SAND report fulfills the completion requirements for the ASC Physics and Engineering Modeling Level 2 Milestone 7836 during Fiscal Year 2021. The Sandia Simplified potential energy clock (SPEC) non-linear viscoelastic constitutive model was developed to predict a whole host of polymer glass physical behaviors in order to provide a tool to assess the effects of stress on these materials over their lifecycle. Polymer glasses are used extensively in applications such as electronics packaging, where encapsulants and adhesives can be critical to device performance. In this work, the focus is on assessing the performance of the model in predicting material evolution associated with long-term physical aging, an area that the model has not been fully vetted in. These predictions are key to utilizing models to help demonstrate electronics packaging component reliability over decades long service lives, a task that is very costly and time consuming to execute experimentally. The initiating hypothesis for the work was that a model calibration process can be defined that enables confidence in physical aging predictions under ND relevant environments and timescales without sacrificing other predictive capabilities. To test the hypothesis, an extensive suite of calibration and aging data was assembled from a combination of prior work and collaborating projects (Aging and Lifetimes as well as the DoD Joint Munitions Program) for two mission relevant epoxy encapsulants, 828DGEBA/DEA and 828DGEBA/T403. Multiple model calibration processes were developed and evaluated against the entire set of data for each material. A qualitative assessment of each calibration's ability to predict the wide range of aging responses was key to ranking the calibrations against each other. During this evaluation, predictions that were identified as non-physical, i.e., demonstrated something that was qualitatively different than known material behavior, were heavily weighted against the calibration performance. Thus, unphysical predictions for one aspect of aging response could generate a lower overall rating for a calibration process even if that process generated better quantitative predictions for another aspect of aging response. This insurance that all predictions are qualitatively correct is important to the overall aim of utilizing the model to predict residual stress evolution, which will depend on the interplay amongst the different material aging responses. The DSC-focused calibration procedure generated the best all-around aging predictions for both materials, demonstrating material models that can qualitatively predict the whole host of different physical aging responses that have been measured. This step forward in predictive capability comes from an unanticipated source, utilization of calorimetry measurements to specify model parameters. The DSC-focused calibration technique performed better than compression-focused techniques that more heavily weigh measurements more closely related to the structural responses to be predicted. Indeed, the DSC-focused calibration procedure was only possible due to recent incorporation of the enthalpy and heat capacity features into SPEC that was newly verified during this L2 milestone. Fundamentally similar aspects of the two material model calibrations as well as parametric studies to assess sensitives of the aging predictions are discussed within the report. A perspective on the next steps to the overall goal of residual stress evolution predictions under stockpile conditions closes the report.
36 MATERIALS SCIENCE↗
Calibration of urban building energy model using smart meter data for district peak load prediction
Urban building energy modeling (UBEM) is a powerful approach to assessing baseline building energy performance and retrofits with new technologies across building stocks in cities. However, the accuracy of UBEM is often constrained by the limited availability of reliable data about building characteristics and operations, such as envelope efficiency levels, HVAC system performance, and end-use load patterns. Existing research has performed UBEM calibration using annual or monthly energy consumption data, which falls short when higher-resolution time series applications are needed, such as peak load prediction for utility operation planning. This study presents a new framework for calibrating building energy models at urban scale using smart meter data, targeting the accurate prediction of summer peak electricity loads to support robust grid planning. The framework first integrates various data sources to enhance baseline input assumptions for building models, and then calibrates the baseline models through a pattern-matching approach. A case study using CityBES and two years of AMI data from over 9000 residential customers in Portland, Oregon, demonstrated the workflow and its effectiveness. The calibrated models achieved a daily peak load mean absolute percentage error of 2.6 % during the heatwave in the calibration year, and 2.0 % in the validation year using another year of AMI data. Using the calibrated models, we analyzed the demand flexibility potential of the district building stock as an application of UBEM calibration. The findings affirm the appropriate use of UBEM for peak electric load forecasting and demand side management at the utility distribution system level.
AMI data↗
Thermal-Mechanical Elastic-Plastic and Ductile Failure Model Calibrations for 6061-T651 Aluminum Alloy from Plate
Numerical simulations of metallic structures undergoing rapid loading into the plastic range require material models that accurately represent the response. In general, the material response can be seen as having four interrelated parts: the baseline response under slow loading, the effect of strain rate, the conversion of plastic work into heat and the effect of temperature. In essence, the material behaves in a thermal-mechanical manner if the loading is fast enough so when heat is generated by plastic deformation it raises the temperature and therefore influences the mechanical response. In these cases, appropriate models that can capture the aspects listed above are necessary. The matters of interest here are the elastic-plastic response and ductile failure behavior of 6061-T651 aluminum alloy under the conditions described above. The work was accomplished by first designing and conducting a material test program to provide data for the calibration of a modular $J_2$ plasticity model with isotropic hardening as well as a ductile failure model. Both included modules that accounted for temperature and strain rate dependence. The models were coupled with an adiabatic heating module to calculate the temperature rise due to the conversion of plastic work to heat. The test program included uniaxial tension tests conducted at room temperature, 150 and 300 C and at strain rates between 10 –4 and 10 3 1/s as well as four geometries of notched tension specimens and two tests on specimens with shear-dominated deformations. The test data collected allowed the calibration of both the plasticity and the ductile failure models. Most test specimens were extracted from a single piece of plate to maintain consistency. Notched tension tests came from a possibly different plate, but from the same lot. When using the model in structural finite element calculations, element formulations and sizes different from those used to model the test specimens in the calibration are likely to be used. A brief investigation demonstrated that the failure model can be particularly sensitive to the element selection and provided an initial guide to compensate in a specific example.
36 MATERIALS SCIENCE↗
Ka-Band ARM Zenith Radar (KAZR) Active Remote Sensing of Clouds (ARSCL) CloudSat Calibration (KAZRARSCL-CLOUDSAT) (Value-Added Product Report)
The Ka-band ARM Zenith Radar Active Remote Sensing of CLouds CloudSat-aligned (KAZRARSCL-CLOUDSAT) Value-Added Product (VAP) applies satellite-based reflectivity calibrations to KAZRARSCL data sets. The Atmospheric Radiation Measurement (ARM) user facility has primarily used radar subsystem calibration monitoring to track cloud radar reflectivity drift over time, since reliable external calibration sources or other absolute references (such as corner reflectors) have historically been unavailable or impracticable. A study by Kollias et al. (2019) examined cloud reflectivity profiles observed with a well-characterized spaceborne downward-pointing millimeter cloud radar, operating as part of NASA’s CloudSat satellite mission (Tanelli et al. 2008). The Kollias team derived monthly statistical reflectivity offsets between CloudSat and the various generations of ARM cloud radars (millimeter wavelength cloud radar [MMCR], W-Band ARM Cloud Radar [WACR[, and Ka-band ARM Zenith Radar [KAZR]) for many, but not all, months at most fixed and mobile ARM sites over the period 2007-2017. These offsets, when available, are applied to the existing KAZRARSCL VAP products using the KAZRARSCL-CLOUDSAT VAP.
54 ENVIRONMENTAL SCIENCES↗
A Numerical Model for Enzymatically Induced Calcium Carbonate Precipitation
Enzymatically induced calcium carbonate precipitation (EICP) is an emerging engineered mineralization method similar to others such as microbially induced calcium carbonate precipitation (MICP). EICP is advantageous compared to MICP as the enzyme is still active at conditions where microbes, e.g., Sporosarcina pasteurii , commonly used for MICP, cannot grow. Especially, EICP expands the applicability of ureolysis-induced calcium carbonate mineral precipitation to higher temperatures, enabling its use in leakage mitigation deeper in the subsurface than previously thought to be possible with MICP. A new conceptual and numerical model for EICP is presented. The model was calibrated and validated using quasi-1D column experiments designed to provide the necessary data for model calibration and can now be used to assess the potential of EICP applications for leakage mitigation and other subsurface modifications.
42 ENGINEERING↗
Decision support for United States—Canada energy integration is impaired by fragmentary environmental and electricity system modeling capacity
The renewable energy transition is leading to increased electricity trade between the United States and Canada, with Canadian hydropower providing firm lower-carbon power and buffering variability of wind and solar generation in the U.S. However, long-term power purchase agreements and transborder transmission projects are controversial, with two of four proposed transmission lines between Quebec, Canada and the northeast U.S. cancelled since 2018. Here, we argue that controversies are exacerbated by a lack of open-source data and tools to understand tradeoffs of new hydropower generation and transmission infrastructure in comparison to alternatives. This gap includes impacts that incremental transmission and generation projects have on the economics of the entire system, for example, how new transmission projects affect exports to existing markets or incentivize new generation. We identify priority areas for data synthesis and model development, such as integrating linked hydropower and hydrologic interactions in energy system models and openly releasing (by utilities) or back-calculating (by researchers) hydropower generation and operational parameters. Publicly available environmental (e.g. streamflow, precipitation) and techno-economic (e.g. costs, reservoir size,) data can be used to parameterize freely usable and extensible models. Existing models have been calibrated with operational data from Canadian utilities that are not publicly available, limiting the range of scientific and commercial questions these tools have been used to answer and the range of parties that have been involved. Studies conducted using highly resolved, national-scale public data exist in other countries, notably, the United States, and demonstrate how greater transparency and extensibility can drive industry action. Improved data availability in Canada could facilitate approaches that (1) increase participation in decarbonization planning by a broader range of actors; (2) allow independent characterizations of environmental, health, and economic outcomes of interest to the public; and (3) identify decarbonization pathways consistent with community values.
13 HYDRO ENERGY↗
SPT clusters with DES and HST weak lensing. II. Cosmological constraints from the abundance of massive halos
We present cosmological constraints from the abundance of galaxy clusters selected via the thermal Sunyaev-Zel’dovich (SZ) effect in South Pole Telescope (SPT) data with a simultaneous mass calibration using weak gravitational lensing data from the Dark Energy Survey (DES) and the Hubble Space Telescope (HST). The cluster sample is constructed from the combined SPT-SZ, SPTpol ECS, and SPTpol 500d surveys, and comprises 1,005 confirmed clusters in the redshift range 0.25–1.78 over a total sky area of 5200 deg 2 . We use DES Year 3 weak-lensing data for 688 clusters with redshifts 𝑧 < 0.95 and HST weak-lensing data for 39 clusters with 0.6 < 𝑧 < 1.7. The weak-lensing measurements enable robust mass measurements of sample clusters and allow us to empirically constrain the SZ observable-mass relation without having to make strong assumptions about, e.g., the hydrodynamical state of the clusters. For a flat Λ CDM cosmology, and marginalizing over the sum of massive neutrinos, we measure Ω m = 0.286 ± 0.032, 𝜎 8 = 0.817 ± 0.026, and the parameter combination 𝜎 8 (Ω m /0.3) 0.25 = 0.805 ± 0.016. Our measurement of 𝑆 8 ≡ 𝜎 8 $\sqrt{Ω_{m}/0.3}$ = 0.795 ± 0.029 and the constraint from Planck CMB anisotropies (2018 TT, TE, EE+lowE) differ by 1.1𝜎. In combination with that Planck dataset, we place a 95% upper limit on the sum of neutrino masses ∑𝑚 𝜈 < 0.18 eV. When additionally allowing the dark energy equation of state parameter 𝑤 to vary, we obtain 𝑤 = −1.45 ± 0.31 from our cluster-based analysis. In combination with Planck data, we measure 𝑤 =−1.34$^{+0.22}_{−0.15}$, or a 2.2𝜎 difference with a cosmological constant. We use the cluster abundance to measure 𝜎8 in five redshift bins between 0.25 and 1.8, and we find the results to be consistent with structure growth as predicted by the Λ CDM model fit to Planck primary CMB data.
79 ASTRONOMY AND ASTROPHYSICS↗
Learning the structure of wind: A data-driven nonlocal turbulence model for the atmospheric boundary layer
In this work, we develop a novel data-driven approach to modeling the atmospheric boundary layer. This approach leads to a nonlocal, anisotropic synthetic turbulence model which we refer to as the deep rapid distortion (DRD) model. Our approach relies on an operator regression problem that characterizes the best fitting candidate in a general family of nonlocal covariance kernels parameterized in part by a neural network. This family of covariance kernels is expressed in Fourier space and is obtained from approximate solutions to the Navier–Stokes equations at very high Reynolds numbers. Each member of the family incorporates important physical properties such as mass conservation and a realistic energy cascade. The DRD model can be calibrated with noisy data from field experiments. After calibration, the model can be used to generate synthetic turbulent velocity fields. To this end, we provide a new numerical method based on domain decomposition which delivers scalable, memory-efficient turbulence generation with the DRD model as well as others. We demonstrate the robustness of our approach with both filtered and noisy data coming from the 1968 Air Force Cambridge Research Laboratory Kansas experiments. Using these data, we witness exceptional accuracy with the DRD model, especially when compared to the International Electrotechnical Commission standard.
17 WIND ENERGY↗
Accelerated Creep Testing of Inconel 718 Using the Stepped Isostress Method (SSM)
This paper demonstrates the stepped isostress method (SSM); an accelerated creep test (ACT) for the rapid assessment of metallic materials. The SSM test is based on the time-temperature-stress superposition principle (TTSSP) where temperature and/or stress are step increased to accelerate the time-to-rupture. The SSM test has proven successful for the ACT of polymers and polymeric composites but has yet to be proven for metallic materials. In this study, new test matrix design rules for the SSM of metals are established based on deformation mechanism, time-temperature transformation, and time-temperature precipitation maps. A test matrix of SSM and conventional creep tests (CCTs) are executed for alloy Inconel 718 at 750°C (1382°F) with stress levels ranging from 100 to 350 MPa. Validation CCT data is gathered from the Japan National Institute of Material Science (NIMS). Material constants for the Sine-hyperbolic (Sinh) constitutive model are calibrated using the SSM data and employed to predict the conventional creep response. Here, when blindly compared to the CCT data, the SSM calibrated Sinh model can accurately predict the conventional creep response across logarithmic decades and thus accelerate the capture of conventional creep data. Fractography indicates ductile fracture by transgranular microvoid coalescence (TMVC) with the same fracture mode observed in both SSM and CCT specimens. Creep cavitation is indicated by the population, smoothness, and size of microvoids.
36 MATERIALS SCIENCE↗
Optode performance data associated with: Metabolic Multireactor: practical considerations for using simple oxygen sensing optodes for high-throughput batch reactor metabolism experiments
This data package is associated with the publication “Metabolic Multireactor: practical considerations for using simple oxygen sensing optodes for high-throughput batch reactor metabolism experiments”, submitted to PlosONE (Kaufman et al. 2023; 10.1101/2023.03.28.534656).We carried out many testing and calibration experiments on a system of small oxygen consumption batch reactors designed for use with water and sediment samples for environmental questions. The oxygen sensing system is based very directly on the work of Larsen, et al. [2011], and similar oxygen sensing technology is widely used in the literature. Our primary focus was on practical considerations, such as temperature effects, lighting angle effects, sterilization, and other similar situations that a user may find useful. Most of the tests required comparing “base” calibration curves to “treatment” calibration curves to determine the extent to which the treatment impacted the reported measurements. This data package contains the performance and calibration data collected for that purpose.This dataset is comprised of one data folder containing (1) file-level metadata; (2) data dictionary; (3) readme; (4) diffusion test result files; (5) limit of detection test result files; (6) temperature impact files; (7) a main data file that contains test results for all other tests; and (8) an R script that uses Kolmogorov-Smirnov tests to determine whether treatment calibrations are significantly different from their respective base calibrations. All files are .csv, .txt, .Rmd, or .pdf.
54 ENVIRONMENTAL SCIENCES↗
Accelerated Creep Test Qualification of Creep-Resistance Using the Wilshire–Cano–Stewart Constitutive Model and Stepped Isostress Method
In this paper, a qualification of accelerated creep-resistance of Inconel 718 is assessed using the novel Wilshire–Cano–Stewart (WCS) model and the stepped isostress method (SSM) and predictions are made to conventional creep data. Conventional creep testing is a long-term continuous process; in fact, the ASME B&PV III requires that 10,000+ h of experiments must be conducted to each heat for materials employed in boilers and/or pressure vessel components. This process is costly and not feasible for rapid development of new materials. As an alternative, accelerated creep testing techniques have been developed to reduce the time needed to characterize the creep resistance of materials. Most techniques are based upon the time-temperature-stress superposition principle that predicts minimum-creep-strain-rate (MCSR) and stress-rupture behaviors but lack the ability to predict creep deformation and consider deformation mechanisms that occur for experiments of longer duration. The SSM has been developed, which enables the prediction of creep deformation response as well as reduce the time needed for qualification of materials. The SSM approach has been successful for polymer, polymeric composites, and recently has been introduced for metals. In this study, the WCS constitutive model, calibrated to SSM test data, qualifies the creep resistance of Inconel 718 at 750 °C and predictions are compared to conventional creep testing data. The WCS model has proven to make long-term predictions for stress-rupture, MCSR, creep deformation, and damage in metallic materials. The SSM varies stress levels after time interval adding damage to the material, which can be tracked by the WCS model. The SSM data is calibrated into the model and the WCS model generates realistic predictions of stress-rupture, MSCR, damage, and creep deformation. The calibrated material constants are used to generate predictions of stress-rupture and are postaudit validated using the National Institute of Material Science database. Similarly, the MCSR predictions are compared from previous studies. Finally, the creep deformation predictions are compared with real data and is determined that the results are well in between the expected boundaries. Material characterization and mechanical properties can be determined at a faster rate and with a more cost-effective method. This is beneficial for multiple applications such as in additive manufacturing, composites, spacecraft, and industrial gas turbines.
42 ENGINEERING↗
ACCELERATED CREEP TEST (ACT) QUALIFICATION OF CREEP RESISTANCE USING THE WCS CONSTITUTIVE MODEL AND STEPPED ISOSTRESS METHOD (SSM)
In this study, a qualification of accelerated creep-resistance of Inconel 718 is assessed using the novel Wilshire-Cano-Stewart (WCS) model and the stepped isostress method (SSM) and predictions are made to conventional creep data. Conventional creep testing (CCT) is a long-term continuous process, in fact, the ASME B&PV III requires that 10,000+ hours of experiments must be conducted to each heat for materials employed in boilers and/or pressure vessel components. This process is costly and not feasible for rapid development of new materials. As an alternative, accelerated creep testing techniques have been developed to reduce the time needed to characterize the creep resistance of materials. Most techniques are based upon the time-temperature-stress superposition principle (TTSSP) that predicts minimum-creep-strain-rate (MCSR) and stress-rupture behaviors but lack the ability to predict creep deformation and consider deformation mechanisms that occur for experiments of longer duration. The stepped isostress method (SSM) has been developed which enables the prediction of creep deformation response as well as reduce the time needed for qualification of materials. The SSM approach has been successful for polymer, polymeric composites, and recently has been introduced for metals. In this study, the WCS constitutive model, calibrated to SSM test data, qualifies the creep resistance of Inconel 718 at 750°C and predictions are compared to CCT data. The WCS model has proven to make long-term predictions for stress-rupture, minimum-creep-strain-rate (MCSR), creep deformation, and damage in metallic materials. The SSM varies stress levels after time interval adding damage to the material, which can be tracked by the WCS model. The SSM data is calibrated into the model and the WCS model generates realistic predictions of stress-rupture, MSCR, damage, and creep deformation. The calibrated material constants are used to generate predictions of stress-rupture and are post-audit validated using the National Institute of Material Science (NIMS) database. Similarly, the MCSR predictions are compared from previous studies. Finally the creep deformation predictions are compared with real data and is determined that the results are well in between the expected boundaries. Material characterization and mechanical properties can be determined at a faster rate and with a more cost-effective method. This is beneficial for multiple applications such as in additive manufacturing, composites, spacecraft, and Industrial Gas Turbines (IGT).
36 MATERIALS SCIENCE↗
Calibrating uncertain parameters in melt pool simulations of additive manufacturing
Melt pool scale numerical modeling of additive manufacturing (AM) processes can provide predictive capabilities and theoretical insight into the process-property-structure-performance relationships for AM parts. Despite capabilities of numerical models to solve complex multi-physics problems, it is often important to consider a tradeoff between detailed physics and computational cost. Therefore, sources of uncertainty in both experimental conditions and the parameters needed for modeling require models to be validated against empirical evidence. Here, a method is proposed to calibrate uncertain parameters used in continuum-scale melt pool models for powder bed fusion (PBF) AM. Both a simplified heat transfer model and a heat transfer and fluid flow model were investigated. A surrogate model and Markov chain-based optimization algorithm calibrated melt pool geometry for models within experimental variation of the target melt pool width and depth from the NIST AM-Bench 2018-02 dataset. The melt pool temperature distributions, solidification parameters, and simulated multi-layer solidification microstructures were compared between the two models. Similar results from both models indicate that calibrated, lower fidelity numerical models may be used in place of higher fidelity models to generate melt pool solidification data. Finally, these calibrated models therefore enable lower computational cost melt pool simulations without a noticeable decrease in simulation accuracy for grain-scale microstructure simulations.
36 MATERIALS SCIENCE↗
Modeling the Impacts of Hydrogen Extraction on Anaerobic Fermentation Systems Using a Modified ADM1 Model
Here, this paper presents a modified ADM1 (mADM1) model for use in assessing the influence of active dissolved H 2 extraction on biogas production from anaerobic fermentation reactors, specifically in the context of high-strength brewery wastewater as the feed. The modified model adds regulation factors to account for the varying product stoichiometry of glucose degradation reactions as a function of H 2 concentration in anaerobic digestion, and incorporates the use of both lactate and ethanol as intermediates. The changes to the model are expected to better predict the effects of H 2 removal on the production of H 2 in fermentation processes. Both ADM1 and mADM1 were calibrated against experimental data from a fluidized-bed reactor containing encapsulated acidogenic-acetogenic microbial communities treating real brewery wastewater. The calibrated models were validated against another fluidized-bed reactor identical to the calibration reactor, with the addition of a hollow-fiber membrane module that was used to reduce dissolved H 2 concentrations in the validation reactor. It was found that ADM1 over-estimated the H 2 production rates of the validation reactor (117 mL/day simulated vs. 16.48 mL/day experimental), whereas mADM1 was able to successfully predict fermentation, and specifically the H 2 production rate (17 mL/day). The presented model is a first step towards a model that can predict the effects of dissolved H 2 removal on fermentation processes.
Anaerobic Digestion↗
Methodology to Calibrate Fragility Curves Using Limited Real-World Data
With increasing human dependence on electricity and increasing energy demand, electrical infrastructure has emerged to be one of the most critical services. This is one of the main reasons for making the power grid more resilient to extreme events during which uninterrupted power supply is crucial in keeping the consequences of the extreme event limited. The first step towards making the overall power grid more resilient is to evaluate the probabilities of failure for all assets at risk from the excitation caused by extreme events. Thus, this paper presents the methodology to calibrate fragility curves. The strength of the proposed approach is its ability to calibrate the fragility curves utilizing limited data, which is the most common constraint in carrying out such analyses. This paper describes the calibration of transmission tower fragility curves for Puerto Rico utilizing only damage reports for hurricane Maria. That, combined with Puerto Rico's wind modeling & geographic information system, this study also calibrates fragility curves for transmission towers made with four different construction materials.
Bereta dos Reis, Fernando↗