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At least 1,621 records · Page 90
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

SU-E-J-273: Skin Temperature Recovery Rate as a Potential Predictor for Radiation-Induced Skin Reactions

Purpose: To assess the potential of dynamic infrared imaging to evaluate early skin reactions during radiation therapy in cancer patients. Methods: Thermal images were captured by our home-built system consisting of two flash lamps and an infrared (IR) camera. The surface temperature of the skin was first raised by ∼ 6 °C from ∼1 ms short flashes; the camera then captured a series of IR images for 10 seconds. For each image series, a basal temperature was recorded for 0.5 seconds before flash was triggered. The temperature gradients (ε) were calculated between a reference point (immediately after the flash) and at a time point of 2sec, 4sec and 9sec after that. A 1.0 cm region of interest (ROI) on the skin was drawn; the mean and standard deviations of the ROIs were calculated. The standard ε values for normal human skins were evaluated by imaging 3 healthy subjects with different skin colors. All of them were imaged on 3 separate days for consistency checks. Results: The temperature gradient, which is the temperature recovery rate, depends on the thermal properties of underlying tissue, i.e. thermal conductivity. The average ε for three volunteers averaged over 3 measurements were 0.64±0.1, 0.72±0.2 and 0.80±0.3 at 2sec, 4sec and 9sec respectively. The standard deviations were within 1.5%–3.2%. One of the volunteers had a prior small skin burn on the left wrist and the ε values for the burned site were around 9% (at 4sec) and 13% (at 9sec) lower than that from the nearby normal skin. Conclusion: The temperature gradients from the healthy subjects were reproducible within 1.5%–3.2 % and that from a burned skin showed a significant difference (9%–13%) from the normal skin. We have an IRB approved protocol to image head and neck patients scheduled for radiation therapy.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Strain shift measured from stress-controlled oscillatory shear: Evidence for a continuous yielding transition and new techniques to determine recovery rheology measures

Understanding the yielding of complex fluids is an important rheological challenge that affects our ability to engineer and process materials for a wide variety of applications. Common theoretical understandings of yield stress fluids follow the Oldroyd–Prager formalism in which the material behavior below the yield stress is treated as solidlike, and above the yield stress as liquidlike, with an instantaneous transition between the two states. This formalism was built on a quasi-static approach to the yield stress, while most applications, ranging from material processing to end user applications, involve a transient approach to yielding over a finite timescale. Using stress-controlled oscillatory shear experiments, we show that yield stress fluids flow below their yield stresses. This is quantified through measuring the strain shift, which is the value about which the strain oscillates during a stress-controlled test and is a function of only the unrecoverable strain. Measurements of the strain shift are, therefore, measurements of flow having taken place. These experimental results are compared to the Herschel–Bulkley form of the Saramito model, which utilizes the Oldroyd–Prager formalism, and the recently published Kamani–Donley–Rogers (KDR) model, in which one constitutive equation represents the entire range of material responses. Scaling relationships are derived, which allow us to show why yield stress fluids will flow across all stresses, above and below their yield stress. Finally, derivations are presented that show strain shift can be used to determine average metrics previously attainable only through recovery rheology, and these are experimentally verified.

Mechanics↗
DOE OSTI2025

Recovery of postconsumer mechanically recycled polymers

Mechanical recycling plays a key role in reducing landfill bound plastics that pollute our environment. This process converts plastic waste into marketable pellets by sorting, cleaning, grinding into flakes, compounding in the molten state, and ultimately pelletizing. A primary restriction for the widescale usage of mechanical recycling is the highly variable quality and mechanical properties of the plastic waste feedstock. Degradation can occur during the plastic life cycle with the consumer, during the mechanical processing itself, or during the complex sorting process required to produce the feedstock. This study explores how rheological characterization can mitigate the batch-to-batch variability and identify a potential application for each batch. Shear and extensional rheology of “application-specific” virgin high-density polyethylene (HDPE) and virgin polypropylene (PP) was used as the control for this categorization process. Recycled HDPE and PP from three different streams were then measured and compared to the results from the control study. Rheological measurements proved to be very effective at providing sufficient differentiation to categorize the recycled polymer as suitable for different applications such as injection molding, blow molding, or thermoforming. Finally, the usage of an additional step to sort the recycled polymers by their initial use application was found to achieve a remarkably consistent recovery of application-specific material properties. Furthermore, this secondary sorting could provide significant added value for mechanically recycled polymers.

Differential scanning calorimetry↗
DOE OSTI2020

Recycling of multilayer plastic packaging materials by solvent-targeted recovery and precipitation

Many plastic packaging materials manufactured today are composites made of distinct polymer layers (i.e., multilayer films). Billions of pounds of these multilayer films are produced annually, but manufacturing inefficiencies result in large, corresponding postindustrial waste streams. Although relatively clean (as opposed to municipal wastes) and of near-constant composition, no commercially practiced technologies exist to fully deconstruct postindustrial multilayer film wastes into pure, recyclable polymers. Here, we demonstrate a unique strategy we call solvent-targeted recovery and precipitation (STRAP) to deconstruct multilayer films into their constituent resins using a series of solvent washes that are guided by thermodynamic calculations of polymer solubility. We show that the STRAP process is able to separate three representative polymers (polyethylene, ethylene vinyl alcohol, and polyethylene terephthalate) from a commercially available multilayer film with nearly 100% material efficiency, affording recyclable resins that are cost-competitive with the corresponding virgin materials.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Pigment removal from reverse-printed laminated flexible films by solvent-targeted recovery and precipitation

The solvent-targeted recovery and precipitation (STRAP) process separates and recovers the constituent resins in multilayer plastic packaging films by selective polymer dissolution. In this work, the cause of coloring in the STRAP-recycled polyethylene (PE) resins from postindustrial printed films was identified as decomposed diarylide pigments. Two different approaches are needed to completely remove the dissolved colorants during the STRAP process including (i) adding an activated carbon (AC) adsorbent to the solvent after polymer dissolution and (ii) proper mechanical filtration of the polymer-solvent cake to remove as much solvent from the cake as possible. Colorless recycled PE can be produced by a combination of the proposed approaches (choosing the proper solvent, adding an AC adsorbent, and doing proper mechanical filtration) with minimal accumulation of colorants in the recycled STRAP solvents. This study demonstrated that high-quality STRAP low-density PE can be obtained from printed plastic films, enhancing the potential circularity of these packaging materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Engineering Cyanobacterial Cell Morphology for Enhanced Recovery and Processing of Biomass

Cyanobacteria are emerging as alternative crop species for the production of fuels, chemicals, and biomass. Yet, the success of these microbes depends on the development of cost-effective technologies that permit scaled cultivation and cell harvesting. Here, we investigate the feasibility of engineering cell morphology to improve biomass recovery and decrease energetic costs associated with lysing cyanobacterial cells. Specifically, we modify the levels of Min system proteins in Synechococcus elongatus PCC 7942. The Min system has established functions in controlling cell division by regulating the assembly of FtsZ, a tubulin-like protein required for defining the bacterial division plane. We show that altering the expression of two FtsZ-regulatory proteins, MinC and Cdv3, enables control over cell morphology by disrupting FtsZ localization and cell division without preventing continued cell growth. By varying the expression of these proteins, we can tune the lengths of cyanobacterial cells across a broad dynamic range, anywhere from an ~20% increased length (relative to the wild type) to near-millimeter lengths. Highly elongated cells exhibit increased rates of sedimentation under low centrifugal forces or by gravity-assisted settling. Furthermore, hyperelongated cells are also more susceptible to lysis through the application of mild physical stress. Collectively, these results demonstrate a novel approach toward decreasing harvesting and processing costs associated with mass cyanobacterial cultivation by altering morphology at the cellular level. We show that the cell length of a model cyanobacterial species can be programmed by rationally manipulating the expression of protein factors that suppress cell division. In some instances, we can increase the size of these cells to near-millimeter lengths with this approach. The resulting elongated cells have favorable properties with regard to cell harvesting and lysis. Furthermore, cells treated in this manner continue to grow rapidly at time scales similar to those of uninduced controls. To our knowledge, this is the first reported example of engineering the cell morphology of cyanobacteria or algae to make them more compatible with downstream processing steps that present economic barriers to their use as alternative crop species. Therefore, our results are a promising proof-of-principle for the use of morphology engineering to increase the cost-effectiveness of the mass cultivation of cyanobacteria for various sustainability initiatives.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

Degradation and recovery of the external quantum efficiency of organic photovoltaic structure

The photosensitivity of a mixed composition of donor CuPc and acceptor C{sub 60}, its degradation in time (for 16 months), and partial recovery (issues that were out of consideration previously) have been investigated. The sample is a simple nanostructure without encapsulation (quartz–SnO{sub 2}–CuPc:C{sub 60}–Al), the degradation of which is easier to analyze. It is shown that the process under study involves two mechanisms: slow (because of the decrease in the carrier lifetime) and relatively fast (because of the decrease in the internal field) degradations of the sample photosensitivity.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2015

Dynamic characteristics of 4H-SiC drift step recovery diodes

The dynamic characteristics of 4H-SiC p{sup +}–p–n{sub 0}–n{sup +} diodes are experimentally studied in the pulsed modes characteristic of the operation of drift step recovery diodes (DSRD-mode). The effect of the subnanosecond termination of the reverse current maintained by electron-hole plasma preliminarily pumped by a forward current pulse is analyzed in detail. The influence exerted on the DSRD effect by the amplitude of reverse-voltage pulses, the amplitude and duration of forward-current pulses, and the time delay between the forward and reverse pulses is demonstrated and accounted for.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Simultaneous Sensing Error Recovery and Tomographic Inversion Using an Optimization-Based Approach

Tomography can be used to reveal internal properties of a 3D object using any penetrating wave. Advanced tomographic imaging techniques, however, are vulnerable to both systematic and random errors associated with the experimental conditions, which are often beyond the capabilities of the state-of-the-art reconstruction techniques such as regularizations. Because they can lead to reduced spatial resolution and even misinterpretation of the underlying sample structures, these errors present a fundamental obstacle to full realization of the capabilities of next-generation physical imaging. In this work, we develop efficient and explicit recovery schemes of the most common experimental error: movement of the center of rotation during the experiment. We formulate new physical models to capture the experimental setup, and we devise new mathematical optimization formulations for reliable inversion of complex samples. We demonstrate and validate the efficacy of our approach on synthetic data under known perturbations of the center of rotation.

Nonlinear optimization↗
DOE OSTI2022

Primary track recovery in high-definition gas time projection chambers

Abstract We develop and validate a new algorithm called primary track recovery () that effectively deconvolves known physics and detector effects from nuclear recoil tracks in gas time projection chambers (TPCs) with high-resolution readout. This gives access to the primary track charge, length, and vector direction (helping to resolve the “head-tail” ambiguity). Additionally, provides a measurement of the transverse and longitudinal diffusion widths, which can be used to determine the absolute position of tracks in the drift direction for detector fiducialization. Using simulated helium recoils in an atmospheric pressure TPC with a 70:30 mixture of $$\hbox {He:CO}_2$$ He:CO 2 we compare the performance of to traditional methods for all key track variables. We find that the algorithm reduces reconstruction errors, including those caused by charge integration, for tracks with mean length-to-width ratios 1.4 and above, corresponding to recoil energies of 20 keV and above in the studied TPCs. We show that improves on existing methods for head-tail disambiguation, particularly for highly inclined tracks, and improves the determination of the absolute position of recoils on the drift axis via transverse diffusion. We find that can partially recover charge structure integrated out by the detector in the z direction, but that its determination of energy and length have worse resolution compared to existing methods. We use experimental data to qualitatively verify these findings and discuss implications for future directional detectors at the low-energy frontier.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2016

Compiler-Directed Soft Error Detection and Recovery to Avoid DUE and SDC via Tail-DMR

This article presents Clover, a compiler-directed soft error detection and recovery scheme for lightweight soft error resilience. The compiler carefully generates soft-error-tolerant code based on idempotent processing without explicit checkpoints. During program execution, Clover relies on a small number of acoustic wave detectors deployed in the processor to identify soft errors by sensing the wave made by a particle strike. To cope with DUEs (detected unrecoverable errors) caused by the sensing latency of error detection, Clover leverages a novel selective instruction duplication technique called tail-DMR (dual modular redundancy) that provides a region-level error containment. Once a soft error is detected by either the sensors or the tail-DMR, Clover takes care of the error as in the case of exception handling. To recover from the error, Clover simply redirects program control to the beginning of the code region where the error is detected. The experimental results demonstrate that the average runtime overhead is only 26%, which is a 75% reduction compared to that of the state-of-the-art soft error resilience technique. In addition, this article evaluates an alternative technique called tail-wait, comparing it to Clover. According to the evaluation with the different processor configurations and the various error detection latencies, Clover turns out to be a superior technique, achieving 1.06 to 3.49× speedup over the tail-wait.

Computer Science↗
DOE OSTI2019

BonVoision: Leveraging Spatial Data Smoothness For Recovery From Memory Soft Errors

The increasing soft error rates in memory systems raise an emerging concern for modern computing systems. As a result, detectable but uncorrectable errors (DUEs) become potentially more frequent and affect HPC applications. Today, upon encountering a DUE, HPC applications crash, incurring significant performance, storage, and energy overheads. In this paper, we propose a technique to continue application execution past a DUE through the repair of the corrupted memory data by leveraging spatial data smoothness. We present BonVoision, a run-time system that intercepts DUE events, analyzes the binary to identify data elements in the structural neighborhood of the event, and fixes the corrupted data elements by interpolating from the values in their neighborhood. Our evaluation demonstrates that BonVoision incurs negligible overhead and outperforms other recovery strategies by a factor of 2×, on average. We demonstrate that BonVoision also improves the efficiency of existing checkpointing/restart schemes by approximately increasing the optimal checkpoint interval by 23%.

Fang, Bo↗
DOE OSTI2023

Frequency Recovery in Power Grids Using High-Performance Computing

Maintaining electric power system stability is paramount, especially in extreme contingencies involving unexpected outages of multiple generators or transmission lines that are typical during severe weather events. Such outages often lead to large supply-demand mismatches followed by subsequent system frequency deviations from their nominal value. The extent of frequency deviations is an important metric of system resilience, and its timely mitigation is a central goal of power system operation and control. This paper develops a novel nonlinear model predictive control (NMPC) method to minimize frequency deviations when the grid is affected by an unforeseen loss of multiple components. Our method is based on a novel multi-period alternating current optimal power flow (ACOPF) formulation that accurately models both nonlinear electric power flow physics and the primary and secondary frequency response of generator control mechanisms. We develop a distributed parallel Julia package for solving the large-scale nonlinear optimization problems that result from our NMPC method and thereby address realistic test instances on existing high-performance computing architectures. Our method demonstrates superior performance in terms of frequency recovery over existing industry practices, where generator levels are set based on the solution of single-period classical ACOPF models.

nonlinear model predictive control↗
DOE OSTI2021

Flow Injection Electrochemical Quartz Crystal Microbalance with ICP-OES Detection: Recovery of Silver by Electrodeposition with Redox Replacement in a Flow Cell

We developed a new on-line hyphenated flow injection analysis technique (FI-EQCM-ICP-OES) that allows electrochemical deposition and stripping with mass detection and elemental analysis. This technique was used to study a new system for electrochemical recovery of silver from a 0.5 mM Ag + /5 mM Cu 2+ /0.5 M H 2 SO 4 solution by pulsed electrodeposition with redox replacement (EDRR) in a small flow cell. The metal ions in a 500 μ l sample are injected into the sulfuric acid carrier stream and deposited onto an electrochemical quartz crystal microbalance (EQCM) electrode housed in a 50 μ l flow cell. The deposits are subsequently stripped off electrochemically in the same cell and analyzed downstream in an ICP-OES. The stripped metal layer was found to be composed of Ag with no detectable Cu for a redox replacement time of 10 s, and 91 wt.% Ag–9 wt.% Cu for a redox replacement time of 5 s. Microscopy measurements demonstrated that the electrode was covered with silver particles, some of which contain Cu in the case of the 5 s replacement time. This technique allowed the study of mass changes on the electrode during electrodeposition and open circuit times in each EDRR cycle in flowing solutions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Electrochemical Recovery of Iron from Spent Pickle Liquor by Chloride-Based Molten Salt Electrolysis

Spent pickle liquor (SPL) is a waste stream generated in the steel industry that presents both a disposal challenge and a potential resource for metal recovery. This study investigates the electrochemical extraction of high-purity iron metal from SPL using chloride-based molten salt electrolysis (CMSE). Electrochemical characterization of diluted SPL confirmed Fe 2+ as the dominant species. Thermal dehydration of SPL under inert atmosphere yielded FeCl 2 -rich solids, which were directly employed as feedstock for electrolysis in LiCl–KCl eutectic melts at 500 °C. Cyclic voltammetry of FeCl 2 in this melt revealed well-defined Fe 2+ /Fe 0 redox behavior within the electrochemical stability window of the supporting electrolyte. High coulombic efficiency (>85%) electrodeposition was achieved demonstrating that iron metal can be produced from dehydrated SPL by CMSE. The electrodeposited iron exhibited >98 wt% purity, which was further enhanced to 99.9 wt% via arc melting. The resulting iron powder was ferromagnetic, and its size distribution was found to be suitable for powder metallurgy applications. This work demonstrates a scalable, energy-efficient pathway for valorizing SPL into high-purity iron metal, advancing circular economy strategies in the steel industry.

Materials science↗
DOE OSTI2022

Pressure Modification or Barrier Issues during Polymer Flooding Enhanced Oil Recovery

Effective oil displacement from a reservoir requires adequate and properly directed pressure gradients in areas of high oil saturation. If the polymer bank is too large or too viscous during a polymer flood, the pressure drops from the injection well to the polymer front may act as a pressure modification or barrier by usurping most of the downstream driving force for oil displacement. Polymer injection pressures must be limited. The maximum allowable injection pressure is commonly constrained by caprock integrity, injection equipment, and/or regulations, even though fractures can be beneficial to polymer injectivity. This paper examines when the pressure-barrier concept limits the size and viscosity of the polymer bank during a polymer flood. Analytical and numerical methods are used to address this issue. We examine the relevance of the pressure modification concept for a wide variety of circumstances, including oil viscosities ranging from 10 cp to 1650 cp, vertical wells versus horizontal wells, single versus multiple layered reservoirs, permeability contrast, and crossflow between layers. We also examine the relation between the pressure-barrier concept and fractures and fracture extension during polymer injection. We demonstrate that in reservoirs with single layers, the pressure-barrier concept only limits the optimum viscosity of the injected polymer if the mobility of the polymer bank is less than the mobility of the displaced oil bank. The same is true for multizoned reservoirs with no crossflow between layers. Thus, for these cases, the optimum polymer viscosity is likely to be dictated by the mobility of the oil bank, unless other factors intervene. For multizoned reservoirs with free crossflow between layers, the situation is different. A compromise must be reached between injected polymer viscosity and the efficiency of oil recovery. This work is particularly relevant to viscous oil reservoirs where polymer viscosities are substantially lower than the oil viscosity.

58 GEOSCIENCES↗
DOE OSTI2019

TOGA: A TOUGH code for modeling three-phase, multi-component, and non-isothermal processes involved in CO2-based Enhanced Oil Recovery (TOGA) v1.0

TOGA (TOUGH Oil, Gas, Aqueous) is a numerical reservoir simulator for modeling non-isothermal flow and transport of water, CO2, multicomponent oil, and related gas components for applications including CO2-enhanced oil recovery (CO2-EOR) and geologic carbon sequestration in depleted oil and gas reservoirs. TOGA uses an approach based on the Peng-Robinson equation of state (PR-EOS) to calculate the thermophysical properties of the gas and oil phases including the gas/oil components dissolved in the aqueous phase, and uses a mixing model to estimate the thermophysical properties of the aqueous phase.

Oldenburg, CurtisM↗
DOE OSTI2022

Storm DEPART(Damage Estimate Prediction And Recovery Tool)

Damage prediction, materials needed, and resource allocation modeling capability in order to support pre-incident planning and preparation by predicting damage to the power generation capacity, transmission grids, distribution networks, and communications assets. The capabilities will be developed by multiple factors to include wind bands, storm surge, and flooding forecasts to participant’s assets which will result in a report of predicted damages. Additional factors to include available participants infrastructure data to include class, age, construction, location, wind rating, and additional information not in the public domain. Based on predicted damages, the output will be a bill of materials (BOM) to support short-term recovery operations. The extensiveness and level of detail for this BOM will depend on the replacement configuration specifications provided for each individual participant asset. Any limiting factors for the model will be applied related supply chain and resource constraints.

Klett, Mary↗