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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 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Water alternative gas (WAG) optimization for a heterogeneous Brazilian pre-salt carbonate reservoir

Water alternating gas (WAG) is a cyclical process that involves alternating water and gas injections with the primary goal to improve sweep efficiency by maintaining initial high pressure, slowing water and gas breakthrough, and lowering oil viscosity. The objective of this work is to apply and optimize a WAG strategy on a carbonate field with light oil, compare it to the initially planned water-flooding strategy, and investigate the capability of WAG to improve field production. In this research, a compositional reservoir simulator was used to model a WAG process by injecting produced gas into the reservoir, using the same well structure as an optimized water-flooding strategy. Subsequently, a WAG strategy was created, optimizing the number and locations of wells, to facilitate a comparative analysis of the two recovery methods. The WAG optimization involved a detailed assessment of variables such as bottom hole pressure (BHP), WAG cycle duration, maximum gas oil ratio (GOR), and well positioning, to achieve a high net present value (NPV). The study focuses on the application of WAG optimization modeling in unconventional reservoirs, specifically pre-salt carbonate reservoirs, and investigates its implications on production strategy and forecast, emphasizing its potential for maximizing NPV and oil recovery in a recently producing field. The results showed that WAG improved reservoir performance when compared to water injection and produced a greater amount of oil. This solution showed potential to be tested under uncertainties (reservoir heterogeneity, faults, fractures, karsts, vugs, etc.) as future steps.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Shifting Left for Machine Learning: An Empirical Study of Security Weaknesses in Supervised Learning-based Projects

Context: Supervised learning-based projects (SLPs), i.e., software projects that use supervised learning algorithms, such as decision trees are useful for performing classification-related tasks. Yet, security weaknesses, such as the use of hard-coded passwords in SLPs, can make SLPs susceptible to security attacks. A characterization of security weaknesses in SLPs can help practitioners understand the security weaknesses that are frequent in SLPs and adopt adequate mitigation strategies. Objective: The goal of this paper is to help practitioners se-curely develop supervised learning-based projects by conducting an empirical study of security weaknesses in supervised learning-based projects. Methodology: We conduct an empirical study by quantifying the frequency of security weaknesses in 278 open source SLPs. Results: We identify 22 types of security weaknesses that occur in SLPs. We observe ‘use of potentially dangerous function’ to be the most frequently occurring security weakness in SLPs. Of the identified 3,964 security weaknesses, 23.79 % and 40.49 % respectively, appear for source code files used to train and test models. We also observe evidence of co-location, e.g., instances of command injection co-locates with instances of potentially dangerous function. Conclusion: Based on our findings, we advocate for a shift left approach for SLP development with security-focused code reviews, and application of security static analysis.

Bhuiyan, Farzana Ahamed↗
DOE OSTI2021

An Active Detection Scheme for Sensor Spoofing in Grid-tied PV Systems

In this paper an active detection scheme for sensor spoofing (manipulated externally via a cyber attack) in grid-tied PV systems is discussed. The core of the proposed active detection scheme is to introduce a private (secret) watermarking signal into the control inputs of the DC-DC converter and DC-AC inverter stages to detect any malicious spoofing (manipulation) of voltage/current sensor measurements controlling both the DC-DC converter maximum power point tracking (MPPT) stage and the DC-AC inverter of the grid-tied PV system. Several types of possible spoofing mechanisms (attack models) are discussed. The proposed sensor spoofing attack detector system consists of injecting a small magnitude of digital watermarking signal (DWS) and conduct three statistical watermark tests on the reported sensor measurements to determine if a) the proposed system is healthy and operating as expected b) if sensor signals were spoofed (manipulated) externally or c) if a particular sensor is malfunctioning due to a faulty hardware. It is shown via extensive simulations that the proposed DWS approach is robust in detecting malicious external manipulation of sensors controlling the grid tied PV system. A testing platform is currently under development and the experimental results will be discussed in the conference presentation.

Ibrahim, Hasan↗
DOE OSTI2019

Convolutional Neural Networks for Heat Flux Model Validation on NSTX-U

To demonstrate the use of embedded thermocouples in new National Spherical Tokamak eXperiment Upgrade (NSTX-U) graphite plasma-facing components (PFCs), a convolutional neural network (CNN) has been trained using the ANSYS simulations to predict the scrape-off layer (SOL) heat flux width, λ q , given various machine operational parameters and diagnostic data as inputs. Here, the proof-of-concept CNN was trained on the thermocouple data generated by the approximated NSTX-U heat loads applied to real PFC designs in ANSYS. Once trained, the CNN is capable of high precision reconstruction of parameterized heat flux profiles expected in NSTX-U. In addition, to test the system's ability to cope with noise and systematic error, pseudonoise was injected into the simulated data. CNN can accurately predict the incident heat flux despite this noise and error.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Industry-Average Performance for Components and Initiating Events at U.S. Commercial Nuclear Power Plants: 2020 Update

This report documents the quantitative results of the current industry-average performance for components and initiating events (IEs) at U.S. commercial nuclear power plants (NPPs). It represents the third update of the original analysis in NUREG/CR-6928 with data through 2020. Continuous characterization and updating of current industry-average performance with the latest industry data available are important steps in maintaining up-to-date risk models. Typically, data from 1998–2002 were used in NUREG/CR-6928, data from 1998–2010 in the first update, data from 1998–2015 in the second update, and data from 2006–2020 in this update, although many IEs required longer periods for adequate characterization of frequencies in all these analyses. As with NUREG/CR-6928 and previous updates, four types of events are covered in this report: component unreliability (e.g., a pump that fails to start or fails to run), component or train unavailability resulting from test or maintenance outages, special event probabilities covering operational issues (e.g., pump restarts and injection valve re-openings during unplanned demands), and IE frequencies. Results (in the form of beta distributions for failure probabilities upon demand and gamma distributions for rates) are used as inputs to the U.S. Nuclear Regulatory Commission standardized plant analysis risk models covering U.S. commercial NPPs.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2021

Hydraulic and Thermal Stimulation Program at Raft River Idaho, A DOE EGS

A Department of Energy Enhanced Geothermal System (EGS) stimulation program has injected over 254 million gallons of water into the well RRG-9 ST1 since the summer of 2013. Three major stimulations have been conducted during the program increasing injection flow rates from less than 20 gpm to 550 gpm. Geologic, water chemistry, microseismic activity, and borehole imaging data have been used to develop a conceptual model describing possible flow paths of this injected water. This model contains two major fracture zones one of which intersects the RRG-9 ST1 wellbore. Modified Hall and injectivity index plots constructed using injection flow rates, surface temperatures, and wellhead pressures show steady improvement in the injectivity of the well. Here, the injectivity index has risen from 0.15 gpm/psi to 2.0 gpm/ psi. A pressure falloff test conducted on April 28, 2015 indicates a reservoir permeability of 1,220 md and -5.38 skin factor. The well stimulation program was simulated numerically using an Idaho National Laboratory reservoir simulation code, FALCON. These simulations show a significant increase in the permeability of connecting fracture pathways after each stimulation event.

Enhanced geothermal system↗
DOE OSTI2023

Building an EPA Class VI Permit Application

Summary To accelerate the commercialization of carbon capture and storage (CCS), the US Department of Energy (US DOE) is building on decades of characterization efforts and pilot-scale projects through their CarbonSAFE program. Administered through their National Energy Technology Laboratory, this program seeks to bring fully integrated projects to the sector that can store more than 50 million tonnes of CO2 over a 30-year period. The program, which was enacted before the enhancement of Internal Revenue Code Section 45Q, is in the capture assessment, characterization, and permitting phase. The objectives of this paper are to discuss (a) the injection permitting requirements of the CarbonSAFE projects; (b) information gathering in support of the permit; (c) the timelines of field development and permit-related activities; (d) the major technical components of the field development plan; and (e) early feedback from the regulators toward acceptance of the permit. In Mississippi, more than 30,000 acres have been characterized by six deep characterization wells, a deep groundwater well, and 92 line miles of 2D seismic as part of the CarbonSAFE Project ECO2S. During the acquisition of seismic data, all receiver lines were live, which resulted in the generation of a pseudo-3D seismic design. The incorporation of a 3D seismic survey was not included as part of this project due to logistical difficulties presented by the undulating, wooded surface terrain. A suite of openhole geophysical logs was taken from each well, allowing for a detailed interpretation of prospective storage reservoirs and confining intervals to complement the analysis carried out on the 290 ft of a whole core that was cut through the prospective confining zone and storage reservoir. The detailed geologic and reservoir data were assembled and entered into a 3D model to assess the injection capacity and the area of review (AoR). This information fed into the detailed corrective action, monitoring, testing, and postinjection site care (PISC) modeling. The results have been exceptional. The geologic assessment has revealed three primary storage targets, ranging in depth from 3,500 ft to 6,000 ft. These storage reservoirs net 1,300 ft of sandstone, with mean porosity and permeability of 29% and 3.6 darcies, respectively. Together, these reservoirs have storage capacities that may exceed 20 million tonnes per square mile, making this a gigatonne prospect. Forward modeling of the project resulted in an AoR of 16 sq miles, injecting about 8000 t/d, for 30 years, via two deep injection wells. The excellent confining characteristics of the caprock, relatively simple geologic structure, and lack of historical well drilling activity in this area provide excellent containment of the injected CO2. Based on this work, the project has proposed 20 years of PISC. To date, only two US CO2 injection permits have been granted. These projects relied on a singular capture point feeding a singular sequestration point (source to sink), and considerations have not been made to garner CO2 emissions from other industrial sources. The Kemper County Storage Complex is a first-of-its-kind storage hub concept that looks to develop an area capable of storing significant quantities of CO2 from the region. Also, this work will show how characterization efforts, geological and numerical modeling efforts, and plan development were constructed in support of permit and incentives acceptance.

Energy & Fuels↗
DOE OSTI2021

Parametric Study of SANSMIC Input and Resulting Impact on Predicted Cavern Geometry and Leaching Efficiency

The Sandia Solution Mining Code (SANSMIC) has been used for many years to examine the development of salt cavern geometry, both in a confirmatory manner with comparisons made to real-world sonar data and in a predictive manner when updated sonar data are not available. SANSMIC models require some modeling choices in order to incorporate real-world data. Key modeling choices include the vertical resolution of cavern geometry to implement, as well as how to incorporate daily raw water injection data into the SANSMIC model. This report documents five studies that address the impact of the modeling choices on the predicted cavern geometries and calculated leaching efficiencies. In most cases, hypothetical cylindrical initial cavern geometries are used to provide a common baseline against which to test the systematic variation of input variables including cavern radius, oil-brine-interface (OBI) depth, vertical cell size, raw water injection rate, raw water injection duration, workover time, and number of leaching stages. The use of smaller cell sizes is recommended moving forward to provide a better one-to-one relationship between sonar data and the modeled cavern. A new methodology for incorporating raw water injection data is also recommended, in order to more closely model real-world injection and workover times. Overall, the systematic studies performed here have increased our confidence in previous SANSMIC model results, as well future use of the code for predicting leaching effects on cavern geometries. Some minor changes to modeling choices are recommended, which can easily be applied with the version of SANSMIC currently under development.

42 ENGINEERING↗
DOE OSTI2019

Test Results of PIP2IT MEBT Vacuum Protection System

The central part of PIP-II program of upgrades pro-posed for the Fermilab injection complex is an 800 MeV, 2 mA, CW-compatible SRF linac. Acceleration in super-conducting cavities begins from a low energy of 2.1 MeV, so that the first cryomodule, Half Wave Resonator (HWR) borders the warm Medium Beam Transport (MEBT) line. To minimize the amount of gas that may enter the SRF linac in a case if a vacuum failure occurs in the warm front end, a vacuum protection system is envisioned to be used in the PIP-II MEBT. It features a fast closing valve with two sensors and a differential pumping insert. The system prototype was installed in the PIP-II Injector Test (PIP2IT) accelerator and successfully tested in several modes modelling the vacuum failures. The report presents the design of the vacuum protection system and results of its tests.

43 PARTICLE ACCELERATORS↗
DOE OSTI2025

Machine Learning-Based Process Control for Injection Molding of Recycled Polypropylene

The increased interest in artificial intelligence in manufacturing has driven the adoption of machine learning to optimize processes and improve efficiency. A key challenge in injection molding is the variability of recycled materials, which affects part quality and processing stability. This study presents a novel closed-loop process control approach for injection molding, leveraging machine learning to adaptively predict processing inputs and quality outcomes. The methodology was tested on five blends of recycled polypropylene (rPP), using artificial neural networks (ANNs), linear regression, and polynomial regression to model the relationships between material properties and process parameters. The dataset was split 80/20 into training and testing sets. The ANN model was implemented using TensorFlow and Keras, with six hidden layers of 32 neurons per layer, ReLU activation, and an Adam optimizer. Empirical tuning and early stopping were used to optimize performance and prevent overfitting. Predictions were evaluated based on mean absolute error (MAE), mean squared error (MSE), and percentage error. The results showed that yield stress, ultimate elongation, and part weight were accurately predicted within a 5% error for linear and polynomial regression models and within a 10% error for the ANN. However, modulus predictions were less reliable, with errors of ~11% for ANN and linear regression and ~40% for polynomial regression, reflecting the inherent variability of this property in rPP blends. Predictions of processing inputs had errors ranging from 3% to 25%, depending on the model and response variable. No single modeling approach was consistently superior across all responses, highlighting the complexity of the relationship between material properties, process parameters, and quality metrics. Overall, the work demonstrates that closed-loop process control, powered by machine learning, can effectively predict key quality parameters in injection molding of recycled materials. The proposed approach can improve process stability and material utilization, facilitating increased adoption of sustainable materials.

Krantz, Joshua↗
DOE OSTI2023

Scaling for Nuclear Reactor System: Overview

A scaling analysis is essential for predicting the behavior of a reactor system under various operating conditions, as well as for ensuring safe and reliable experimentation and adequate dataset generation for supporting the system code model development and assessment in accordance with USNRC guidelines 1.203. Testing and modeling can be carried out at various scales, from small test units to full-scale reactors, to validate the predictions produced by the analysis. However, due to the cost and challenges associated with full-scale testing, the nuclear industry uses scaled test facilities—integral effect test (IET) and separate effect test (SET)—to identify potential design issues and optimize the design to ensure regulatory compliance for safer operation and anticipated accident management. In general, IET facilities are non-nuclear thermal hydraulics test facilities. In contrast, SET facilities can be non-nuclear testing (e.g., steam generator, containment, pump system SETs) and nuclear testing (mostly fuel-material irradiation testing). IETs are used to study the system-level thermal-hydraulic behavior of the reactor coolant system (RCS) under different anticipated operational occurrences (AOOs) and design basis accidents (DBAs) such as loss-of-coolant-accident (LOCA) and loss-of-power (i.e., station blackout) and loss-of-flow (i.e., failure of RCS pump). Several LOCA scenarios could happen in reactor DBAs, such as main steam line break (MSLB), SG tube rapture (SGTR), break in direct vessel injection (DVI), and other small breaks LOCA. Scaling analysis determines the appropriate size and operating conditions for the test facility. This involves analyzing the system's thermal-hydraulic behavior at different scales and identifying the key parameters that affect the thermal-hydraulic behavior of the reactor. These key parameters can be identified so that the scaled facility can replicate the expected conditions in a prototypical setting. The scaled facility can simulate the same flow rates, pressure gradients, heat transfer coefficients, and fluid properties as the prototype. Scaling analysis is used to ensure that the results from these tests can be scaled up to predict the behavior of a full-scale prototype with an acceptable range of scaling distortions.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2020

Ducted Fuel Injection versus Conventional Diesel Combustion: An Operating-Parameter Sensitivity Study Conducted in an Optical Engine with a Four-Orifice Fuel Injector

Ducted fuel injection (DFI) has been shown to attenuate engine-out soot emissions from diesel engines. The concept is to inject fuel through a small tube within the combustion chamber to enable lower equivalence ratios at the autoignition zone, relative to conventional diesel combustion. Previous experiments have demonstrated that DFI enables significant soot attenuation relative to conventional diesel combustion for a small set of operating conditions at relatively low engine loads. This is the first study to compare DFI to conventional diesel combustion over a wide range of operating conditions and at higher loads (up to 8.5 bar gross indicated mean effective pressure) with a four-orifice fuel injector. This study compares DFI to conventional diesel combustion through sweeps of intakeoxygen mole fraction (XO 2 ), injection duration, intake pressure, start of combustion (SOC) timing, fuel-injection pressure, and intake temperature. DFI is shown to curtail engine-out soot emissions at all tested conditions. Under certain conditions, DFI can attenuate engine-out soot by over a factor of 100. In addition to producing significantly lower engine-out soot emissions, DFI enables the engine to be operated at low-NO x conditions that are not feasible with conventional diesel combustion due to high soot emissions.

42 ENGINEERING↗
DOE OSTI2021

Cybersecurity of Wide Area Monitoring, Protection and Control Systems for HVDC Applications

The flexibility provided by High Voltage Direct Current (HVDC) systems can be further extended by Wide Area Monitoring, Protection, and Control (WAMAPC) systems. WAMPAC systems enable many HVDC applications and, on the other hand, inevitably introduce cybersecurity concerns that need to be addressed. In this work, a security domain layer and decision framework is reported to detect and mitigate the impact of false data injection (FDI) attacks targeting HVDC stations. Specifically, a rule-based cyber-attack detection method is introduced and implemented on Raspberry Pi and tested on the real-time HVDC simulation facility on the real-time digital simulator (RTDS) platform at ABB U.S. Corporate Research Center.

cybersecurity↗
DOE OSTI2019

Beam Tests of the PIP-II Injector Test Radio Frequency Quadrupole

In modern high intensity ion-particle accelerators, a Radio Frequency Quadrupole (RFQ) is utilized to prepare a high-quality beam for injection to the main accelerating section. Since an RFQ governs the initial beam parameters, characterization of the beam coming out from the RFQ is foremost step toward commissioning of an accelerator facili-ty. It allows validating the RFQ design as well as attaining a better understanding of charged-particle beams. This pa-per describes the beam-performance of the Proton Improvement Plan-II Injector Test (PIP2IT) Continuous Wave (CW) four vane-type RFQ. It is designed to operate at a frequency of 162.5 MHz and accelerate a nominal H- beam of 5 mA from 30 keV to 2.1 MeV. The paper details beam tests performed to validate the RFQ design specifications for trans-mission, beam kinetic energy and, RMS emittances. The paper also presents beam profile measurements and implica-tion of the beam-jitters on the effective beam emittance at the RFQ exit.

43 PARTICLE ACCELERATORS↗
DOE OSTI2019

Application of deoxygenation-aeration cycling to control the predatory bacterium Vampirovibrio chlorellavorus in Chlorella sorokiniana cultures

A previously untested approach was evaluated to enable management of the predatory bacterium, Vampirovibrio chlorellavorus, a pathogen of Chlorella sorokiniana, in suspension cultures grown in a laboratory test reactor. Because V. chlorellavorus is an obligate aerobic bacterium, whereas C. sorokiniana grows under aerobic and anaerobic conditions, deoxygenation of the culture was expected to be detrimental to the pathogen, but not to the algal host. The effect of deoxygenation on the uninfected (healthy) C. sorokiniana suspension cells, compared to the C. sorokiniana-V. chlorellavorus co-culture, was studied in relation to biomass, dissolved oxygen, ratio of C. sorokiniana to V. chlorellavorus DNA, and visual and light microscopic observations. Preliminary experiments were conducted to test the effects of different deoxygenation-aeration cycling regimes on performance of V. chlorellavorus-free C. sorokiniana cultures. To an aerobic culture, pure nitrogen gas was introduced to create anoxic conditions, followed by the injection of ambient air to re-establish an aerobic environment. Under this repeated cycling regime, C. sorokiniana was shown to tolerate the anoxic conditions for extended timespans that ranged from 2 to 8 h over a 5-day test period. The analogous aerobic-anoxic cycling with the C. sorokiniana-V. chlorellavorus co-cultures resulted in ‘near-normal’ growth cycle and harvestable biomass, whereas the continuously-aerated (aerobic) co-cultures that were grown without the deoxygenation step in the cycle collapsed in 3 days. Visual and light microscopic observations revealed intact C. sorokiniana cells were present in the deoxygenated cultures, compared to the aerobically-grown, brown-colored algal cultures consisting of collapsed cells. Quantitative polymerase chain reaction analysis showed continuous increases in the ratio of V. chlorellavorus (16S rDNA) to C. sorokiniana (18S rDNA) DNA in the aerated co-cultures, with greater increases during dark periods, while the pathogen-to-host DNA ratio in the deoxygenated co-cultures was relatively low and algal cells did not collapse, as would be expected following pathogen attack.

Algae, Anoxic, Bomass, Infection, Nitrogen, Quanti↗
DOE OSTI2026

Storage Field Development Plan: One Earth Energy

This Storage Field Development plan presents the Storage Complex characterization results, construction, monitoring, and operational plans, and costs associated with the proposed One Earth Sequestration Carbon Capture and Storage (OES-CCS) site in McLean County, Illinois, near Gibson City. The proposed storage complex, known as the Mt. Simon Storage Complex, comprises the Cambrian Mt. Simon Sandstone reservoir and the primary seal, the Cambrian Eau Claire Formation. The lowermost Underground Source of Drinking Water (USDW) identified for the site is the Ordovician St. Peter Sandstone. Geologic characterization of the Mt. Simon Storage Complex at the OES-CCS site was performed by the Illinois Storage Corridor CarbonSAFE Phase III project, which also prepared and submitted three UIC Class VI applications to construct three injection wells; the permit applications were submitted and are in the federal EPA review process. A characterization well, OEE #1, was drilled to collect site-specific data. These data were analyzed and used to develop the UIC Class VI applications. The OEE #1 well will be converted to an in-zone monitoring (IZM) well for the injection phase. The proposed buildout for the OES-CCS site includes (1) three injection wells (OES #1, OES #2, and OES #3), (2) two IZM wells, (3) two above confining zone (ACZ) monitoring wells, one of which will be used to monitor the lowermost USDW, (4) capture and compression facilities, and (5) transportation facilities, i.e., pipelines. A pre-operational testing program was proposed in the Class VI permit application and will be employed at the site pending approval. Additional pre-injection (baseline), syn-injection, and post-injection monitoring and site care procedures will be followed by OES to ensure that injection activities are protective of human health and the environment. Injection is scheduled to begin in 2025, distributed across the three injection wells in accordance with the permit operating conditions. One Earth Sequestration intends to inject up to 90 million tonnes of CO 2 over a period of approximately 20 years. Injection will begin at approximately 0.5 million tonnes of CO 2 annually and ramp up to a maximum of 4.5 million tonnes annually. Daily injection rates are expected to range from 1,400 to 1,500 tonnes per day initially and reach a maximum of approximately 4,225 tonnes per day, depending on site geology and injectivity at each injection well location, and CO 2 availability. The costs associated with the OES-CCS project include pre-operational costs (e. g. additional seismic data acquisition and well drilling), capture and transportation facility and equipment costs, predicted field operating expenditures (OpEx), and decommissioning and post-injection site care (PISC) costs. The risks associated with project activities, such as site construction, injection operations, and verification of secure storage were evaluated, and mitigation strategies proposed to alleviate those risks.

09 BIOMASS FUELS↗
DOE OSTI2018

Role of capsaicin sensitive sensory nerves in ischemia reperfusion-induced acute kidney injury in rats

Highlights: • The sensory neuropeptides of CGRP and SP significantly increased after renal IR injury in kidney. • The large dose of capsaicin treatment in neonatal rats resulted in degeneration of capsaicin sensitive sensory nerves. • The degeneration of capsaicin sensitive sensory nerves and the reduction of CGRP and SP aggravated IR-induced AKI in rats. • The degeneration of capsaicin sensitive sensory nerves activated the ERK signal pathway of spinal cord and kidney. Acute kidney injury (AKI) is a common kidney disorder which is associated with a high risk of mortality. Extensive evidence revealed the participation of renal afferent sensory nerves in the pathophysiology of renal ischemia reperfusion (IR) injury, however the role of these nerves in renal IR injury is controversial and remains to be further explored. Here, we report that capsaicin sensitive sensory nerves and neuropeptides prevented renal damage in AKI induced by IR injury. The sensory afferent degeneration model was established by injecting 50 mg/kg of capsaicin to male neonatal rats and verified by the tail flick test and reduced sensory neuropeptide of substance P and calcitonin gene related peptide in spinal cord, dorsal root ganglion and kidney after 12 weeks. Then, a model of renal IR injury was established. The sensory afferent degeneration in the AKI group increased the level of serum creatinine, NGAL and KIM-1, aggravated to some extent renal pathological damage, and enhanced the proinflammatory cytokines expressions and tubular cell apoptosis. In addition, it was also discovered that the level of phospho-ERK/ERK (p-ERK/ERK) showed an increase in spinal cord and kidney after degeneration of capsaicin sensitive sensory nerves. In conclusion, the degeneration of sensory nerves aggravated IR-induced AKI in rats, and the activated ERK signaling in spinal cord and kidney after sensory afferent degeneration might be the possible mechanism in the aggravated renal injury.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

The effect of ICRH and NBI on tungsten transport in neon edge radiation cooled discharges in TEXTOR

Tungsten is planned to be the plasma-facing material for the main chamber and divertor in future devices like ITER, SPARC, and DTT. To address risks associated with tungsten, R&D is being carried out on various toroidal confinement devices. One particular research question is related to the optimum heating mix for ITER. To investigate the influence of the heating scheme on the release and transport of tungsten, a comparison of neutral beam injection (NBI) and ion cyclotron resonance frequency (ICRF) heating was carried out in TEXTOR tungsten test limiter experiments. The experiments were performed under standard L-mode conditions and in radiative improved-mode operation with neon seeding and boronized walls covering the graphite plasma-facing components. The plasma was heated with hydrogen or deuterium NBI alone or with deuterium NBI in combination with H-minority, ion cyclotron resonance heating. A movable solid tungsten limiter was inserted through a limiter lock system into the edge plasma. The impurity release from this limiter was evaluated from visible spectroscopy. The tungsten concentrations in the plasma core were determined by extreme ultraviolet spectroscopy and bolometry. With deuterium NBI alone, strong central radiation and accumulation of W was observed. This can, however, be avoided by adding ICRF heating.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗