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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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Excel spreadsheet describing activity, spending, and development for the four data hubs (Arizona Geoloical Survey, Kentucky Geological Survey, Illinois Geological Survey, and Nevada Bureau of Mines and Geology) serving data for the National Geothermal Data System under the State Contributions to the National Geothermal Data System Project.
The objectives of this study were to identify the transportation and logistics challenges, assess the associated impacts, and provide recommendations for strategies and specific actions to address the challenges.
The State of Alaska has a rather unique electric power system, as it has two larger transmission grids (Railbelt and Southeast Alaska) and over 150 islanded stand-alone power systems that are serving remote rural communities. In 2010, the Alaska legislature enacted a non-binding goal for 50% of renewable electricity generation by 2025. With the expected increase in wind and solar generation in the future, the role of energy storage becomes increasingly important. Considering the specific power system characteristics in Alaska, energy storage technologies that can supply electricity over an extended period of time, such as pumped storage hydropower (PSH), may play a key role in enabling the reliability and resiliency of both integrated and rural power systems. The overarching objective of the subject study of this presentation is to investigate the prospects and opportunities for PSH in Alaska.
Abstract To reach the goals set by the US Department of Energy's Sustainable Aviation Fuel (SAF) Grand Challenge, currently available feedstocks may be insufficient. Giving priority to developing, prototyping and reducing the cost of algal feedstock before investing and lining up locations is important. As the production of algal feedstocks advances, a simplified conversion approach using more mature technologies can help reduce the investment risk for algae‐based fuels. Reducing process complexity to the steps described here [namely, conversion of lipids to HEFA (hydroprocessed esters and fatty acids) fuels and relegating the remainder of the biomass to anaerobic digestion or food/feed production] enables the near‐term production of algal SAF but presents challenging economics depending on achievable cultivation costs and compositional quality. However, these economics can be improved by present‐day policy incentives. With these incentives, the modeled algae‐to‐HEFA pathway could reach a minimum fuel selling price as low as $4.7 per gasoline gallon equivalent depending on the carbon intensity reduction that can be achieved compared with petroleum. Uncertainty about algal feedstock production maturity in the current state of technology and the future will play a large role in determining the economic feasibility of building algae‐to‐HEFA facilities. For example, if immaturity increases the feedstock price by even 10%, SAF production in 2050 is about 58% of the production which could have been achieved with mature feedstock. Additionally, growth in this conversion pathway can be notably boosted through the inclusion of subsidies, and also through higher‐value coproducts or higher lipid yields beyond the scope of the process considered here.
Abstract not provided
Although Tribal land represents more than 5% of the solar photovoltaic technical potential in the United States, this resource is largely untapped due to a range of barriers, including complex project economics, Tribal technical and human resource capacity, project funding and financing obstacles, and regulatory challenges. To identify and better understand the regulatory barriers, the National Renewable Energy Laboratory (NREL) and the Midwest Tribal Energy Resources Association (MTERA) engaged Tribes, utilities, and regulators. Funded by the U.S. Department of Energy, the 3-year effort seeks to address regulatory challenges or barriers that affect Tribal solar projects differently - specifically or disproportionately because they are located on Tribal lands. This paper, largely excerpted from a comprehensive (draft) guidebook released by NREL and MTERA, provides an overview of 13 key regulatory barriers identified through this research, as well as potential short- and long-term solutions. In addition, the paper points to potential pathways for addressing key barriers through case studies highlighting successful Tribal solar projects along with considerations for stakeholders working with Tribes. These resources can support stakeholders in creating meaningful relationships and pursuing workable solar projects.
TMS conference proceedings
Abstract not provided.
Stenting in intracranial atherosclerotic disease (ICAD) is increasingly debated, due to issues of procedural safety, technical efficacy, and in-stent recurrent stenoses (ISR). In the present study, feasibility, safety, and efficacy of angioplasty using a drug-eluting balloon (DEB) followed by the implantation of a self-expanding stent (Enterprise) were evaluated for the treatment of ICAD lesions. Fifty-two patients (median age: 71 years; range: 54-86 years; male/female ratio 37:15) underwent stenting of high-grade ICAD lesions between February 2010 and November 2011 in a single center. Angioplasty using a paclitaxel coated SeQuent Please (B. Braun, Germany) or DIOR (Eurocor, Germany) coronary PTCA balloon, followed by the implantation of a self-expanding stent (Enterprise, Codman, USA) was performed in 54 lesions. Angiographic and clinical follow-up was performed at 6 and 12 weeks, 6 and 12 months, and yearly thereafter. Technical success rate, periprocedural complications, occurrence of recurrent ischemic symptoms, and the development of an ISR were analyzed. Angioplasty using a DEB followed by stent implantation was successfully performed in 44 (81 %) cases. DEB insertion failed in 19 % of the cases and angioplasty was finally performed using a conventional PTCA balloon. The combined procedure related permanent neurologic morbidity and mortality rate (stroke, ICH, and subarachnoid hemorrhage) at 30 days and beyond was 5 %. Angiographic and clinical follow-up were obtained in 33 (61 %) lesions in 32 patients. Recurrent stenosis was seen in one (3 %) lesion. Angioplasty and stenting using a DEB is safe and yields encouragingly low ISR rates. Further technical developments to improve lesion accessibility are, nevertheless, mandatory.
No abstract prepared.
IntroductionThe imaging features of unresectable hepatic malignancies in patients who underwent radiofrequency ablation (RFA) in combination with lyso-thermosensitive liposomal doxorubicin (LTLD) were determined.Materials and MethodsA phase I dose escalation study combining RFA with LTLD was performed with peri- and post- procedural CT and MRI. Imaging features were analyzed and measured in terms of ablative zone size and surrounding penumbra size. The dynamic imaging appearance was described qualitatively immediately following the procedure and at 1-month follow-up. The control group receiving liver RFA without LTLD was compared to the study group in terms of imaging features and post-ablative zone size dynamics at follow-up.ResultsPost-treatment scans of hepatic lesions treated with RFA and LTLD have distinctive imaging characteristics when compared to those treated with RFA alone. The addition of LTLD resulted in a regular or smooth enhancing rim on T1W MRI which often correlated with increased attenuation on CT. The LTLD-treated ablation zones were stable or enlarged at follow-up four weeks later in 69 % of study subjects as opposed to conventional RFA where the ablation zone underwent involution compared to imaging acquired immediately after the procedure.ConclusionThe imaging features following RFA with LTLD were different from those after standard RFA and can mimic residual or recurrent tumor. Knowledge of the subtle findings between the two groups can help avoid misinterpretation and proper identification of treatment failure in this setting. Increased size of the LTLD-treated ablation zone after RFA suggests the ongoing drug-induced biological effects.
Nowadays, data generated by large-scale scientific experiments are on the scale of petabytes per month. These data are transferred through dedicated high-bandwidth networks (40/100G) across distributed sites for processing, storage, and analysis. Like general purpose networks, research networks experience intrusions. However, monitoring anomalies in such high-speed network traffics is challenging given current cyber-infrastructure. Moreover, traditional network intrusion detection systems (NIDS) are signature based. However, anomaly patterns are difficult to define and that rulesets are often not updated frequently enough to reflect the changes of attack behaviors. We present ThunderSecure, a high-throughput, unsupervised learning-based intrusions detection system for 100G research networks. ThunderSecure implements an efficient packet processing and detection pipeline using multi-cores and GPUs. It extracts statistical and temporal features from real-time network data streams and feeds them to a one-class anomaly detection network. A baseline of normal distribution will be created based on the training observation. Testing traffic deviated from the learned profile will be marked as anomalies. We trained ThunderSecure on hundreds of billions of science data packets mirrored from two 100G network connections at Fermi National Accelerator Laboratory. The detection performance was evaluated on traffic captured from the same research network days and weeks after the training with different types of attack flows injected. Results show that ThunderSecure can recognize science data traffic captured long after the training and made nearly certain detection on the segment of the streams where anomalous flows were injected.
POLARBEAR-2b (PB-2b) is the second receiver in the Simons Array, a cosmic microwave background (CMB) polarization experiment. The Simons Array uses dichroic polarization sensitive lenslet-coupled sinuous antennas and transition-edge sensor (TES) bolometers made of superconducting films. These bolometers are read out with frequency multiplexing electronics. PB-2b contains ~7500 detectors in two bands at 90 and 150 GHz with arcminute resolution. The polarization of these detectors is modulated by a cryogenic continuously rotating half-wave plate. PB-2b was installed on its telescope in 2022 in the Atacama Desert at an altitude of 5.2 km. This paper will detail initial readout commissioning, test of a new loopgain monitoring method, and focusing the optics. Work is ongoing to commission the remaining ambient temperature readout electronics, measure detector time constants, and observe with the cryogenic half-wave plate spinning.
Plug-in electric vehicles (PEVs), including battery electric vehicles (BEVs) and plug-in hybrid electric vehicles (PHEVs), have been promoted globally for their emission reductions and energy conservation. In addition to financial incentives for PEVs in many countries (Stephens et al. 2018), emission and energy regulatory systems provide additional incentives for PEVs in the USA, Europe, and China (European Union 2014; Innovation Center for Energy and Transportation 2019; U.S. EPA and NHTSA 2012). These incentives, together with PEV technology advances and cost reductions, have caused PEV sales to grow exponentially in many countries and global regions; PEV stocks totaled more than 5 million by the end of 2018 (Fig. 1). The International Energy Agency (2019) projects that PEV sales will grow even more quickly through 2030 to reach a total global PEV stock of 130 million to 250 million.
No abstract provided.
The paper was presented at the 33rd European Symposium on Computer Aided Process Engineering (ESCAPE33) June 18-21, 2023, in Athens, Greece.
The capability to utilize neural networks to predict macroscopic and microscopic cross section parametric spaces has been developed for the Griffin reactor physics application. The LibTorch interface enables Griffin's MOOSE-based materials to interact with LibTorch-trained models, allowing for the evaluation of complex macroscopic or microscopic cross section spaces, which are then used to evaluate the neutronic properties of the Griffin finite element model. This study benchmarks traditional ISOXML-formatted tabulation libraries against neural network-based models for 279 nuclides on 20,160 grid points for zero-dimensional and two-dimensional reactor models. Benchmark metrics include the fundamental mode eigenvalue, fission and absorption rates, and various temperature coefficients of reactivity (isothermal, fuel, and moderator). From the perspective of storage space, the complete set of LibTorch models uses 11 MB on disk, compared to the 10 GB for the ISOXML multigroup library that covers the same grid space. For the two-dimensional performance case considered in Griffin, the Torch model uses 97% less RAM than the reference ISOXML dataset while runtime increases by a factor of 3 when using the LibTorch model compared to the ISOXML dataset with multi-linear interpolation. The LibTorch model consistently yields errors within 0.01% for most analyzed quantities except for the temperature coefficients of reactivity where the maximum discrepancies are up to 0.3 $\frac{pcm}{K}$. Due to the neural network attempting to best predict quantities with no regard for a positive or negative bias for any given quantity, predictions may experience random fluctuations, resulting in both positive and negative errors. Future work will entail both depletion and coupled transient analysis to determine the predictive capabilities of Griffin with neural network-based cross sections.