Block Gram-Schmidt algorithms and their stability properties
Not Available
SEARCH · Engineering Papers
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.
Not Available
Here we present a set of algorithms built on the MTEX and MATLAB graph toolboxes for automatic reconstruction of deformation twin hierarchies from Electron Backscatter Diffraction (EBSD) datasets with a focus on developing methods for heavily twinned microstructures (twin fractions >0.5). The algorithms address key issues arising at large strains, mainly: missing twin relationships, grouping of heavily deformed grain fragments into families of similar orientation originating from a single initial grain, identification of parent fragments for large twin volume fractions, and classification of families having twin relationships with multiple families. To facilitate the development of these algorithms, large-grained ultra-high purity α-Ti deformed in compression along two directions is investigated. Graphs are utilized to handle non-local geometric merging and to represent relationships throughout the reconstruction process. When determining if a grain fragment is from the undeformed microstructure, the combined metrics of the fragment's orientation volume fraction in the initial texture and the directed graph centrality measure of out-closeness (the number of nodes reached in a graph from a given node) are essential. To address automation in reconstructing the sequence of twinning and relating fragments originating from a single grain in the initial microstructure, the twin family tree is formulated as a minimum spanning tree emanating from the initial grain family. A scheme constructing the distances associated with twin relationship comprising the spanning tree is developed, and a novel quasi-directional Prim spanning tree algorithm is used to determine the twin family tree. The procedure is demonstrated to significantly improve the level of automation in reconstructing twin hierarchies in heavily twinned microstructure compared to other methodologies in literature. The procedure can readily be applied to analyses of twinning in metals, as well as provide an approach for routinely extracting twin statistics at larger deformation levels than previously possible. Significantly, the procedure is demonstrated to be capable of identifying third generation twinning in α-Ti microstructures.
This paper presents a first-principles model for the recovery of dissolved gases from liquids using a sidestream hollow-fiber membrane module. The model avoids the use of new empirical coefficients, thus providing a parametric understanding of the process behavior for future design and optimization of membrane modules. This type of first-principles model could be particularly useful when gas recovery is beneficial to biological or chemical reactions of interest, such as the acetogenesis reactions in two-stage anaerobic digesters. The steady-state behavior of the model was validated against both new experimental data for the recovery of H 2 , CH 4 and H 2 –CH 4 mixtures from pure water, as well as existing published data. The modeled gas recovery predictions agreed with experimental data to an absolute average error of 13%, and an average R value of 0.98. Parametric analysis of mixed-gas recovery suggests possible key transition points in the composition of the recovered gases. For example, at 40 °C, increasing trans-membrane pressure while keeping hydraulic residence time (HRT) under 0.5 s will result in an increase in the ratio of H 2 to CH 4 recovered. Otherwise, increasing trans-membrane pressure will instead decrease the ratio of H 2 to CH 4 recovered. The model has potential to be extended to transient analysis, but has yet to be validated with transient experimental data. Furthermore, this model was successfully implemented in both Python and MATLAB, and provides valuable insights for future net-energy optimization for anaerobic digestion systems with in-situ gas recovery.
In order to demonstrate acceleration of electrons to relativistic scales by an on chip dielectric laser accelerator (DLA), a ponderomotive focusing scheme capable of capturing and transporting electrons through nanometer-scale apertures over extended interaction lengths has been proposed. Here we present a Matlab-based numerical code (SHarD) utilizing a spatial harmonic expansion of the fields within the dielectric structure to simulate the evolution of the beam phase space distribution in this scheme. The code can be used to optimize key-parameters for the accelerator performance such as the final energy, transverse spot size evolution and total number of electrons accelerated through currently fabricated structures. Eventually, the simulation model will be applied to inform the phase mask profile to be added to a pulse front tilt drive laser pulse using a liquid crystal mask in the experimental setup being assembled at UCLA Pegasus Laboratory.
Here REX, an analytical reactor design tool for the identification and expansion of reactor operating envelopes, is introduced and detailed. Written in MATLAB, REX takes core geometries and axially discretized detector and depletion output from the Serpent neutron transport code and performs full-core, pin-specific thermal-hydraulic and thermo-mechanical calculations. REX identifies the operating envelopes of advanced, solid-fuel nuclear reactors on the basis of their fuel-cladding, fuel-gas, and coolant-cladding interfacial thermo-mechanics. It iteratively pushes coolant inlet temperatures and modifies fuel pin geometries to induce mechanical failure in their original cladding materials at the fullest extent of their fuel cycle lengths and permissible coolant inlet temperatures. It then attempts to expand their operating envelopes by determining the mechanical responses of alternative cladding materials under the same geometric conditions. The result of the REX calculation sequence is a set of 5-D variables describing the temperatures, pressures, geometries, and mechanics of the core as functions of assembly, fuel pin, axial zone, depletion step, and coolant inlet temperature for each candidate cladding material with the limiting fuel pin geometry for the original material.
A prototypical natural circulation water-based reactor cavity cooling system (RCCS) for the UC Berkeley Mark-1 pebble-bed gFHR is designed based on one-dimensional thermal hydraulics modeling and optimization implemented in an in-house MATLAB code. The model employs a lumped core consisting of fuel pebble and graphite pebble regions, while the graphite reflector, vessel, and RCCS are represented as separate but energy-coupled regions. The model is derived based on steady state energy balance equations accounting for conductive heat transfer from the lumped core to the vessel and subsequent radiative heat transfer to the RCCS and convective heat transfer in the water. Further, mass flow rate is calculated based on momentum and thermal energy balance in the RCCS. Starting with ANL’s water NSTF as baseline, effects of RCCS design parameters such as size of the plate between pipes, pipe diameter, source-to-sink distance, surface emissivity, and pitch from the core are examined in an integral effects framework which accounts for subsequent variation of the mass flow rate, number of pipes, convection coefficient, mean region and surface temperatures, radiative view factors, and water outlet temperature. The importance of including a prototypical reactor design in RCCS design calculations is emphasized as the calculations show that temperature drops from the core to the RCCS fluid to transfer the heat tend to be the limitation not the heat removal capacity of the fluid. A closed-loop design is obtained with capability to safely remove up to 0.72% of the nominal reactor power at maximum estimated peak conditions and 0.40% at shutdown. The design is based on physics calculations and does not account for economic optimization.
This work developed designs of submerged, dual-regions, miniature DC-EM pumps for circulating molten lead and liquid sodium at ≤500 °C without active cooling for use in ex-pile and in-pile test loops to support of materials and fuel developments for Gen-IV sodium and molten lead fast nuclear reactor. These pumps with two pumping regions are 57 mm, 66.8 mm, 95.4 mm, and 133.5 mm in diameter and have two Alnico 5 permanent magnets with Hiperco-50 pole pieces for focusing the magnetic field lines in the flow duct. The Equivalent Circuit Model (ECM) linked to the Finite Element Method Magnetics (FEMM) software in MATLAB platform calculated the pumps characteristics for a wide range of parameters. Also determined are the pumps dimensions for the highest cumulative pumping power and peak efficiency. These dimensions are the height, width, and length of the flow duct, the thickness of the Alnico magnets, the length of current electrodes, and the separation distance between the two pumping regions. For molten lead, the pumping power increases from 368 W to 728 W, and the peak efficiency from 14.7% to 31.6% with increased pump diameter from 57 mm to 133.5 mm. In conclusion, for liquid sodium, both the pumping power and peak efficiency are higher, increasing from 392 W to 767 W and from 44.3 to 51.2%, respectively, with increased pump diameter from 57 mm to 133.5 mm.
Accurate prediction of second-order hydrodynamic loads is essential for floating bodies, including floating offshore wind turbines, wave energy converters, and hybrid wind–wave platforms. These nonlinear effects, arising from both sum- and difference-frequency forcing, are critical for capturing key response characteristics but remain challenging to model efficiently. In this work, we extend the open-source Wave Energy Converter Simulator / MATLAB for Offshore Simulation Tool by implementing second-order wave excitation forces, supporting both the full Quadratic Transfer Function formulation and the Newman approximation. The full Quadratic Transfer Function method is used for all code-to-code comparisons and experimental validation, while the Newman approximation is provided as a computationally lighter alternative. To benchmark the new capability, we perform a code-to-code comparison with OpenFAST and OrcaFlex. We then validate the enhanced model using wave-tank measurements of a 1:96 scale DeepCwind semi-submersible, showing that second-order effects are required to reproduce platform motions. The implementation employs a computationally efficient pre-computation strategy for second-order wave excitation forces, reducing simulation cost while maintaining engineering accuracy. Overall, this work advances the tool as an open-source and versatile tool for modelling floating offshore renewable-energy systems requiring second-order hydrodynamic fidelity.
Permeability k and formation factor F are important petrophysical properties that have broad applications to reservoir engineering. Although well-log analysis has advanced reservoir characterizations, direct measurement of k is still not available. Accordingly, resistivity logs and more particularly formation factor have been frequently used to estimate k. In this study, we present a theoretical framework to relate k to F. We use power-law scaling from continuum percolation theory to develop a theoretic relationship between k and F, which is similar in form to a published power-law equation with empirical coefficients. Our result gives a physical interpretation to this empirical relationship. We also compare power-law scaling laws from percolation theory with data derived from experimental measurements and numerical simulations in the literature. Finally, using the Curve Fitting toolbox of MATLAB, the parameters of the power-law equations are determined, and the significance of the non-universal power laws are discussed.
This paper describes the first uncertainty analysis for drilling stability using a frequency-domain drilling stability model. The stability model inputs include: the modal parameters for the torsional-axial vibration mode from the twist drill-holder-spindle axial frequency response function; and the mechanistic coefficients that relate the torque and thrust force to chip area for the selected drill-workpiece material combination. Furthermore, Monte Carlo simulation is applied to propagate the input uncertainties to output uncertainty in the predicted stability map, which separates stable from unstable (chatter) zones in the spindle speed-chip width parameter space. Additionally, the mean stability boundary and its 95% confidence intervals are determined for five cases: varying all four inputs simultaneously and varying them individually. This enables the individual sensitivities to be compared. Experimental results from drilling tests are included for comparison to the prediction. Additionally, Matlab code is provided to implement the stability model and Monte Carlo uncertainty analysis.
The power take-off (PTO) system in a wave energy converter (WEC) is the means by which the energy in an ocean wave is converted into useful energy. There has been a general lack of technology convergence in the wave energy industry and PTO design has been largely device-specific with the design process determined by the WEC developer. An optimized PTO design can significantly affect the efficiency, reliability, performance, and overall cost and viability of a device. There remains a need in the marine energy industry for best practices and efficient design processes to be identified as it could greatly benefit developers and researchers in designing an optimal WEC PTO. This research utilizes the open-source Matlab-Simulink based software, WEC-Sim, which was developed by the National Renewable Energy Laboratory, and the Eagle, a high-performance computing system, to model and optimize two WECs of different archetypes and then investigates if any trends exist that can be exploited for greater efficiency in optimal PTO design. The results from this research indicate that there may be an optimal sizing for WEC PTOs for both power and PTO force rating and that substantial reductions can be made in the cost of a device without significant loss in the energy produced. Furthermore this optimal sizing may be independent of WEC type and deployment location. With an optimal, or near optimal, approach to WEC PTO sizing demonstrated, a methodology is proposed to address the challenge of nameplate ratings in the wave energy industry.
Soil zymography is commonly used to quantify spatial distribution of hydrolytic enzyme activities on soil and plant root surfaces. It is recommended to adjust pH in zymography substrates and calibration solutions with respect to soil/root pH. However, pH values may vary greatly within a few mm of plant rhizosphere, potentially altering the distribution of pH in zymography membranes. Despite the fact that the effect of pH on the calibration of zymography membranes is generally known, its potential impact on zymography results is unaccounted for in processing zymography images and calculations of enzyme activity. In this study we assessed the effect of pH variations on the persistency of the methylumbelliferone (MUF) calibration. The studied pH values ranged from 4.5 to 7.5. The MUF calibration curves greatly deviated from that at a reference pH of 6.5, with a marked nonlinear increase of deviation with greater membrane brightness. We suggest that the problem can be partially alleviated by reducing the membrane incubation time. However, such deviations suggest the need for a more comprehensive resolution via mapping pH and using pH-specific calibrations to process zymography images. Here, we developed a MATLAB code to implement a pixel-based correction of enzyme activity for pH in processing time-lapse zymography images.
The accumulation of carbon dioxide (CO 2 ) within enclosed spaces, along with volatile organic compounds, under certain humidity, temperature, and ventilation conditions is associated with detrimental human health symptoms such as fatigue. Color-based chemical sensing is a promising approach to detect CO 2 levels relevant to indoor air quality through producing fast, quantifiable output visible to the naked eye. In a prior work, a colorimetric gas sensor was fabricated through synthesizing the metal-organic framework, ZIF-8, as the adsorbent, followed by post-synthetic mixing with a dye, phenol red (PSP), and primary amine, ethylenediamine (ED). While this sensor (termed PSP-ED/ZIF-8) maintained its structural integrity in atmospheric conditions and exhibited an increasing fuchsia-to-yellow color change with increasing CO 2 levels in dry environment, the colorimetric response greatly suffered in the presence of humid CO 2 . Here in this work, a significantly improved colorimetric CO 2 sensor (referred to as ED/PSP:ZIF-8) is accomplished through directly incorporating phenol red in the ZIF-8 metal and linker precursor solutions and then blending with ethylenediamine. MATLAB-generated color distributions and in-situ ultraviolet-visible (UV-Vis) spectroscopic studies quantitatively demonstrate an enhanced colorimetric gas response of ED/PSP:ZIF-8 compared to that of PSP-ED/ZIF-8 across an important range of CO 2 for indoor air quality monitoring (500 – 3500 ppm) and across a range of humidity. The new sensor also exhibits high selectivity to CO 2 compared to select volatile organic compounds, such as acetone and ethanol, which contribute to human health symptoms experienced indoors. The enhanced performance is attributed to the proposed incorporation of phenol red within ZIF-8, while maintaining the chemical stability of the MOF.
A laser-debonding approach to silver electrode recovery from solar cells is presented to address the critical need for efficient and eco-friendly recycling methods. The study explores the use of UV nanosecond and IR continuous-wave lasers to precisely debond silver electrodes from silicon wafers. By optimizing parameters like laser power, scan speed, and the number of passes, intact silver electrical contact lines were recovered from solar cells. Scanning electron microscopy with energy-dispersive X-ray spectroscopy (SEM-EDS) analysis confirmed the successful separation of silver from silicon wafers. Furthermore, an increase in the number of laser passes led to the production of silver microparticles, as validated by morphology and compositional studies using EDS. The estimated silver is approximately 90 mg for the Si solar cells of 15.4 * 15.4 cm 2 used in the study. To achieve a large area recovery of silver, a MATLAB code incorporating detection algorithms and specific criteria to automate laser scanning by accurately identifying the location of silver electrodes was developed. This presented laser debonding method is not confined to silicon solar cells but can be extended to other solar cell types featuring metal electrodes, offering a versatile solution. By minimizing the use of hazardous chemicals and reducing operational costs, the developed process aligns with the imperative of environmentally responsible photovoltaic waste management.
Capacitive deionization (CDI) devices use cyclical electrosorption on porous electrode surfaces to achieve water desalination. Process modeling and design of CDI systems requires accurate treatment of the coupling among input electrical forcing, input flow rates, and system responses including salt removal dynamics, water recovery, energy storage, and dissipation. Techno-economic analyses of CDI further require a method to calculate and compare between a produced commodity (e.g. desalted water) versus capital and operational costs of the system. In this work, we demonstrate a new modeling and analysis tool for CDI developed as an installable Matlab program that allows direct numerical simulation of CDI dynamics and calculation of key performance and cost parameters. The program is provided for free and is used to run open-source Simulink models. The Simulink environment sends information to the program and allows for a drag and drop design space where users can connect CDI cells to relevant periphery blocks such as grid energy, battery, solar panel, waste disposal, and maintenance/labor cost streams. The program allows for simulation of arbitrary current forcing and arbitrary flow rate forcing of one or more CDI cells. We employ validated well-mixed reactor formulations together with a non-linear circuit model formulation that can accommodate a variety of electric double layer sub-models (e.g. for charge efficiency). The program includes a graphical user interface (GUI) to specify CDI plant parameters, specify operating conditions, run individual tests or parameter batch-mode simulations, and plot relevant results. The techno-economic models convert among dimensional streams of species (e.g. feed, desalted water, and brine), energy, and cost and enable a variety of economic estimates including levelized water costs.
Genome-scale stoichiometric modeling of metabolism has become a standard systems biology tool for modeling cellular physiology and growth. Extensions of this approach are emerging as a valuable avenue for predicting, understanding and designing microbial communities. Computation of microbial ecosystems in time and space (COMETS) extends dynamic flux balance analysis to generate simulations of multiple microbial species in molecularly complex and spatially structured environments. Here we describe how to best use and apply the most recent version of COMETS, which incorporates a more accurate biophysical model of microbial biomass expansion upon growth, evolutionary dynamics and extracellular enzyme activity modules. In addition to a command-line option, COMETS includes user-friendly Python and MATLAB interfaces compatible with the well-established COBRA models and methods, as well as comprehensive documentation and tutorials. Overall, this protocol provides a detailed guideline for installing, testing and applying COMETS to different scenarios, generating simulations that take from a few minutes to several days to run, with broad applicability to microbial communities across biomes and scales.
A challenge for data sharing in systems neuroscience is the multitude of different data formats used. Neurodata Without Borders: Neurophysiology 2.0 (NWB:N) has emerged as a standardized data format for the storage of cellular-level data together with meta-data, stimulus information, and behavior. A key next step to facilitate NWB:N adoption is to provide easy to use processing pipelines to import/export data from/to NWB:N. Here, we present a NWB-formatted dataset of 1863 single neurons recorded from the medial temporal lobes of 59 human subjects undergoing intracranial monitoring while they performed a recognition memory task. We provide code to analyze and export/import stimuli, behavior, and electrophysiological recordings to/from NWB in both MATLAB and Python. The data files are NWB:N compliant, which affords interoperability between programming languages and operating systems. This combined data and code release is a case study for how to utilize NWB:N for human single-neuron recordings and enables easy re-use of this hard-to-obtain data for both teaching and research on the mechanisms of human memory.
Land and Earth system modeling is moving towards more explicit biophysical representations, requiring increasing variety of datasets for initialization and benchmarking. However, researchers often have difficulties in identifying and integrating non-standardized datasets from various sources. We aim towards a standardized database and one-stop distribution method of global datasets. Here, we present the GriddingMachine as (1) a database of global-scale datasets commonly used to parameterize or benchmark the models, from plant traits to vegetation indices and geophysical information and (2) a cross-platform open source software to download and request a subset of datasets with only a few lines of code. The GriddingMachine datasets can be accessed either manually through traditional HTTP, or automatically using modern programming languages including Julia, Matlab, Octave, Python, and R. The GriddingMachine collections can be used for any land and Earth modeling framework and ecological research at the regional and global scales, and the number of datasets will continue to grow to meet the increasing needs of research communities.