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At least 361 records · Page 20

All sources NASA NTRS DOE OSTI

DOE OSTI2021

Control systems and methods to enable autonomous drilling

Buerger, Stephen↗

DOE OSTI2022

Control systems and methods to enable autonomous drilling

A system or method for drilling includes autonomously controlling a rotary or percussive drilling process as it transitions through multiple materials with very different dynamics. The method determines a drilling medium based on real-time measurements and comparison to prior drilling data, and identifies the material type, drilling region, and approximately optimal setpoint based on data from at least one operating condition. The controller uses these setpoints initially to execute an optimal search to maximize performance by minimizing mechanical specific energy. Near-bit depth-of-cut estimations are performed using a machine learning prediction deployed in an embedded processor to provide high-speed ROP estimates. The sensing capability is coupled with a near-bit clutching mechanism to support drilling dysfunction mitigation.

Buerger, Stephen↗

DOE OSTI2023

Control systems and methods to enable autonomous drilling

Buerger, Stephen↗

DOE OSTI2023

Redox-Based Chemical Looping Large-Scale Air Separation Unit Designs Using Perovskite Material

Oxygen production by means of air separation through redox cycle reactions of Sr 1–x Ca x FeO 3-δ perovskite particles is examined numerically in the context of modular large-scale units. Fixed-bed, multicomponent reactor designs allowing for the recovery of the energy released by the exothermic oxidation (or adsorption) to enhance the endothermic reduction (or desorption) of the perovskite material are considered and compared against a baseline cylindrical packed bed. Numerically, the gas–solid reacting system is approximated as a single-phase reacting gas flow through a porous medium of constant porosity. The redox kinetics account for the oxygen nonstoichiometry of the perovskite, which exhibits a dependence on the temperature and the oxygen partial pressure, in order to describe some mechanisms of the oxygen vacancies. Results show that the spontaneous release of the oxygen from the lattice arrangements, through the thermal management of the heat of the oxidation reaction from the geometrical design of the reactors, can be enhanced up to 4% with respect to the baseline oxygen production of 0.201 g O 2 ·h –1 ·g perovskite –1 with the cylindrical packed bed, in the condition of operations in this work, at 500 °C. Sensitivity to the operation temperature showed that the oxygen production is greatly enhanced by approximately 30% with the increase of the temperature from 500 to 550 °C. We report this result is consistent with experimental observations of faster release of the oxygen from the lattice arrangements of this perovskite at 550 °C.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

In-flight positional and energy use data set of a DJI Matrice 100 quadcopter for small package delivery

Abstract We autonomously directed a small quadcopter package delivery Uncrewed Aerial Vehicle (UAV) or “drone” to take off, fly a specified route, and land for a total of 209 flights while varying a set of operational parameters. The vehicle was equipped with onboard sensors, including GPS, IMU, voltage and current sensors, and an ultrasonic anemometer, to collect high-resolution data on the inertial states, wind speed, and power consumption. Operational parameters, such as commanded ground speed, payload, and cruise altitude, were varied for each flight. This large data set has a total flight time of 10 hours and 45 minutes and was collected from April to October of 2019 covering a total distance of approximately 65 kilometers. The data collected were validated by comparing flights with similar operational parameters. We believe these data will be of great interest to the research and industrial communities, who can use the data to improve UAV designs, safety, and energy efficiency, as well as advance the physical understanding of in-flight operations for package delivery drones.

42 ENGINEERING↗

DOE OSTI2021

Project 57 Air Monitoring Report: January 1 through September 30, 2020, with a Review of the Period of Record Radionuclide Analyses

The DOE Environmental Management Nevada Program (EM NV) identified the Project 57 contaminated area as Corrective Action Unit (CAU) 415, Project 57 No. 1 Plutonium Dispersion Site, which consisted of one Corrective Action Site (CAS): NAFR-23- 02, Pu Contaminated Soil (U.S. DOE, 2014). The CAS included several Project 57 operational facilities in addition to the plutonium-contaminated soil. With approval of the State of Nevada Division of Environmental Protection, the DOE closed the Project 57 surface soil contamination site in October 2020. Closure was accomplished by installing a clean soil cap constructed over ground zero and the surrounding areas of the CA that may be entrained with wind-transported soil particles. After completion of the ground zero cap in October 2020, DRI discontinued monitoring of meteorological and associated environmental conditions at the Project 57 site as directed by DOE EM NV. Navarro dismantled air monitoring stations P57-3 and P57-4 and removed the equipment on October 20, 2020. This report presents the meteorological and dust observations and radiological analyses accomplished during the approximately 10 months when the air monitoring data collection equipment was operational during CY2020.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Lessons learned from the design and operation of a small-scale cross-flow tidal turbine

In 2023, a first-generation prototype of a small-scale marine current turbine was operated in Sequim Bay, Washington (USA) for 141 days. The system, referred to as the Turbine Lander, was the product of a laboratory-to-field effort to develop a system that enables enhanced ocean sensing or vehicle recharge in remote, energetic settings. The turbine consists of a vertical-axis, cantilevered rotor (1.19 m x 0.85 m) with four foils installed on a gravity foundation. A broader range of constraints including the deployment strategy, site characteristics, and estimated loads, drove the system’s design. This work presents the design, characterization, operation, and post-recovery engineering assessment of the Turbine Lander. Pre-deployment characterization efforts yielded a peak power coefficient of approximately 0.3 for the rotor, although system losses resulted in much lower water-to-wire efficiencies under most operating conditions. The results demonstrate the importance of co-design among key components of the powertrain and control systems to achieve acceptable system efficiency across operating conditions.

Co-design↗

DOE OSTI2026

Thermal Reservoir Networks for Modularly Expandable Thermal Microgrids

The Department of Defense (DoD) faces the substantial challenge of cost-effectively retrofitting one to two installations per month, each comprising approximately 1,000 buildings, to improve resilience, reduce energy consumption, and enhance energy supply security. Achieving these objectives requires optimal system selection and effective risk mitigation during system integration. To address this need, we introduce Platform-Based Design (PBD), a structured, hierarchical methodology adapted from other industrial sectors to the domain of energy system retrofits. We demonstrate the effectiveness of PBD through a techno-economic feasibility study comparing geothermal-coupled thermal energy networks (TENs) with conventional energy systems for heating, cooling, and powering 17 buildings at Joint Base Andrews (JBA) in Maryland. Our analysis illustrates that the PBD approach enables rigorous, data-driven, sequential decision making, resulting in a family of Pareto-optimal systems, among which the TEN emerged as the most promising solution. The selected TEN design integrates geothermal borefields, heat recovery heat pumps, photovoltaic (PV) arrays, and battery storage. Compared to the baseline system – gas heating combined with air-source chillers – the proposed TEN reduces annual imported energy by 74% and peak electricity demand by 45%, achieves a levelized cost of energy of $\$0.210$/kWh, and substantially enhances resilience. Life-cycle costs increase by approximately 6%, and initial investment costs are about 2.5 times higher than the baseline. However, if central plant infrastructure, district loops, and utility-scale PV and battery systems are privately funded and operated, the initial investment would fall below the baseline system cost. Critical to achieving these significant performance improvements were detailed nonlinear dynamic simulations coupling geothermal heat transfer, energy system operation, and realistic feedback control logic. These simulations identified essential design modifications and control strategy refinements that substantially reduced energy use, peak demand, and compressor shortcycling, thereby improving durability and reliability—issues that would have been significantly more expensive to resolve during operation. Additionally, the verification step highlighted sensitivities to key design parameters that could reduce initial investment by approximately $\$2$ million and reduce annual life-cycle costs more than $\$300,000$. We recommend adopting the PBD methodology for future feasibility studies and TEN pilot projects to gain valuable operational experience. Furthermore, we recommend that DoD invest in transferring and scaling the PBD methodology to other installations. This entails developing standardized computational frameworks and component libraries as well as training industry in conducting PBD. Such investments would enable rapid, robust, reliable, and cost-effective retrofits, supporting DoD’s ambitious energy system modernization goals.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2020

Application of Koopman operator for model-based control of fracture propagation and proppant transport in hydraulic fracturing operation

This work explores the application of the recently developed Koopman operator approach for model identification and feedback control of a hydraulic fracturing process. Controlling fracture propagation and proppant transport with precision is a challenge due in large part to the difficulty of constructing approximate models that accurately capture the characteristic moving boundary and highly-coupled dynamics exhibited by the process. Koopman operator theory is particularly attractive here as it offers a way to explicitly construct linear representations for even highly nonlinear dynamics. The method is data-driven and relies on lifting the states to an infinite-dimensional space of functions called observables where the dynamics are governed by a linear Koopman operator. Here this work considers two problems: (a) fracture geometry control, and (b) proppant concentration control. In both cases, an approximate linear model of the corresponding dynamics is constructed and used to design a model predictive controller (MPC). The manuscript shows that in the case of highly nonlinear dynamics, as observed in the proppant concentration, use of canonical functions in the observable basis fails. In such cases, a priori system knowledge can be leveraged to choose the required basis. The numerical experiments demonstrate that the Koopman linear model shows excellent agreement with the real system and successfully achieves the desired target values maximizing the oil and gas productivity. Additionally, due to its linear structure, the Koopman models allow convex MPC formulations that avoid any issues associated with nonlinear optimization.

42 ENGINEERING↗

DOE OSTI2026

Evaluation of thermal energy storage for central receiver concentrating solar power plants under charging cycles through structural assessment

Electricity production by concentrated solar power (CSP) systems has stood out among energy transition alternatives due to their large generation capacity (between 30 MW and 400 MW) and high capacity factor (80%) when incorporating thermal storage systems (TES). Although TES tanks in operation worldwide are made of austenitic steels with remarkable mechanical and anticorrosive properties, operational failures have been reported due to low-cycle fatigue, creep, and the abrupt release of residual stresses generated during tank manufacturing. A critical operation for salt tanks is the initial daily charging operation, given the low fluid level and the thermal gradients between the inventory and the salt entering the tank. This study presents a structural simulation of a 39.6 m-diameter molten salt tank for central receiver CSP plants, accounting for temperature and pressure variations during charging and different sparger ring inlet configurations. The initial pre-stressed condition of the floor, resulting from the manufacture of welded plates, is used as a boundary condition. The fatigue and creep life analyses were performed in accordance with the ASME BPVC and API standards. It was found that the tank's floor is in a less favourable mechanical condition than the wall, due to its initial manufacturing condition and the maximum temperature differences during charging. A critical zone was identified in an area affected by residual stress on the floor and under the sparger ring. The baseline sparger ring configuration, with 52 2-inch-diameter orifices and a flow direction of 90 degrees , results in an average floor stress of approximately 25 MPa and creep damage after 1.2 years of tank operation.

14 SOLAR ENERGY↗

DOE OSTI2020

Overview of the Long-Term Stewardship of the Remediated Uranium Mining and Milling Sites in Europe - 20079

Uranium mining in Europe began in the ' 40's for civil and military applications. The great majority of the uranium mines have now been closed and are going through the stages of decommissioning and/or rehabilitation. Today, the main uranium producers are outside the EU; only a few mines are still in operation inside the EU. In 2006, the situation of the uranium mines and mill tailings in Europe, identifying the tailings liabilities, their status, the plans for these sites and any associated hazards, was reported to the EC. The legacy of uranium mines and mill tailing disposals in the EU are located mainly in 12 Member States where, in total, 87 tailing objects were identified at 63 sites. The volume of each one of these tailings disposal varies from a few thousand to several tens of million m{sup 3}. The majority of these sites are no longer in operation. More than 40 tailing embankments have already been completely remediated. Approximately 20 are currently being remediated while for the remaining objects, remediation has yet to start. After ten years, and for a few cases where the respective projects have not yet been completed, it seems that most of Europe's uranium mines and milling legacies were remediated according to acceptable environmental standards. Nevertheless, Europe is about to face a new challenge that comes from the concluded remediation projects for which an effective set of measures for coordinated institutional control, known as 'long-term stewardship', is needed including, in most cases, continuous and active maintenance. Moreover, the uncertainty of what will happen to these sites if institutional control fails at some point in time is a major concern. This work presents a summary of the situation and current issues of the uranium mine and mill tailings in Europe and their remediation status. It addresses not only the management of existing uranium mine and mill legacies but also the methods and strategies that have been used to prevent the creation of new future legacy sites from uranium mines still in operation. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2023

Data-driven quantum approximate optimization algorithm for power systems

Abstract Quantum technology provides a ground-breaking methodology to tackle challenging computational issues in power systems. It is especially promising for Distributed Energy Resources (DERs) dominant systems that have been widely developed to promote energy sustainability. In those systems, knowing the maximum sections of power and data delivery is essential for monitoring, operation, and control. However, high computational effort is required. By leveraging quantum resources, Quantum Approximate Optimization Algorithm (QAOA) provides a means to search for these sections efficiently. However, QAOA performance relies heavily on critical parameters, especially for weighted graphs. Here we present a data-driven QAOA, which transfers quasi-optimal parameters between weighted graphs based on the normalized graph density. We verify the strategy with 39,774 expectation value calculations. Without parameter optimization, our data-driven QAOA is comparable with the Goemans-Williamson algorithm. This work advances QAOA and pilots its practical application to power systems in noisy intermediate-scale quantum devices.

Jing, Hang (ORCID:0000000256343489)↗

DOE OSTI2026

What do physics-informed DeepONets learn? Understanding and improving training for scientific computing applications

Physics-informed deep operator networks (DeepONets) have emerged as a promising approach toward numerically approximating the solution of partial differential equations (PDEs). In this work, we aim to develop further understanding of what is being learned by physics-informed DeepONets by assessing the universality of the extracted basis functions and demonstrating their potential toward model reduction with spectral methods. Results provide clarity about measuring the performance of a physics-informed DeepONet through the decays of singular values and expansion coefficients. In addition, we propose a transfer learning approach for improving training for physics-informed DeepONets between parameters of the same PDE as well as across different, but related, PDEs where these models struggle to train well. This approach results in significant error reduction and learned basis functions that are more effective in representing the solution of a PDE.

Deep operator networks↗

DOE OSTI2020

Implementation of the Glycolate Destruction Process with Sodium Permanganate in the Defense Waste Processing Facility (DWPF) - 20141

The Savannah River Site (SRS) seeks to replace formic acid with glycolic acid as a chemical reductant in the Defense Waste Processing Facility (DWPF), where borosilicate glass is mixed with high-level radioactive waste, melted at high temperatures, then poured into stainless steel canisters for safe storage. Prior research and development have demonstrated the feasibility and advantages of the new nitric-glycolic acid flowsheet over the current nitric-formic acid flowsheet to chemically adjust the radioactive sludge slurry waste in the Sludge Receipt and Adjustment Tank (SRAT) prior to vitrification. Use of glycolic acid reduces hydrogen and ammonia generation during the reduction process, thus reducing flammability hazards and purge requirements in the DWPF processing vessels. In addition, glycolic acid will support the new Salt Waste Processing Facility (SWPF) by allowing for receipt of higher volumes of waste due to reduction of flammable gases, increased boil-up rates in the vessels, and easing the processing of future sludge batches containing high levels of mercury. However, during DWPF operations, trace amounts of glycolate are anticipated to be entrained in the recycle stream and sent to the Concentration, Storage, and Transfer Facilities (CSTF) via the Recycle Collection Tank (RCT). The RCT receives condensate from the Slurry Mix Evaporator Condensate Tank (SMECT) and Off-gas Condensate Tank (OGCT) that may contain unreacted glycolate. A literature review found the potential for hydrogen generation due to thermolysis of glycolate in caustic CSTF conditions. Savannah River National Laboratory (SRNL) conducted several tests on simulant and radioactive waste from various tanks at SRS and confirmed that glycolate added to waste at concentrations of approximately 1000 mg/L and higher generates hydrogen through thermolysis. There are potential operating scenarios in the future where glycolate concentration could exceed 1000 mg/L in the 2H Evaporator Drop Tank, the highest accumulation point for DWPF organics received via recycle. These findings presented a need to develop another process to mitigate the impact of glycolic acid to the CSTF. Several DWPF compatible options were evaluated for their ability to destroy glycolate in the DWPF recycle stream under various processing conditions, thereby mitigating its introduction to the CSTF. Downselection testing identified sodium permanganate as the most promising and simplest option to oxidize glycolate. It has been demonstrated to be effective in various RCT simulant compositions, operating temperatures, oxidant addition rates, solution pH, and initial glycolate concentrations. A feasibility study identified existing tanks within the facility that could be used for receiving and storing the commercially available sodium permanganate, as well as feeding it to the RCT for processing. The use of existing equipment as well as the ability to purchase the pre-mixed chemical reduces implementation and operational complexity. The downstream impacts of the sodium permanganate reaction were also evaluated and demonstrated to have minimal impact on other chemical species present in the RCT and CSTF, as well as on the materials of construction of the RCT and CSTF vessels and associated piping and instrumentation. Future work is in progress to validate the glycolate destruction process with testing in actual radioactive RCT waste before implementation in DWPF. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2022

Learning stochastic dynamics with statistics-informed neural network

We introduce a machine-learning framework named statistics-informed neural network (SINN) for learning stochastic dynamics from data. This new architecture was theoretically inspired by a universal approximation theorem for stochastic systems, which we introduce in this paper, and the projection-operator formalism for stochastic modeling. Here, we devise mechanisms for training the neural network model to reproduce the correct statistical behavior of a target stochastic process. Numerical simulation results demonstrate that a well-trained SINN can reliably approximate both Markovian and non-Markovian stochastic dynamics. We demonstrate the applicability of SINN to coarse-graining problems and the modeling of transition dynamics. Furthermore, we show that the obtained reduced-order model can be trained on temporally coarse-grained data and hence is well suited for rare-event simulations.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2026

Spatially Accelerated Winding Numbers for Curved Geometry

The generalized winding number (GWN) is a scalar field that supports robust containment queries on curved geometry, including non-watertight, overlapping, and nested boundary representations. While queries can be easily parallelized over samples, direct evaluation on parametric curves and surfaces remains costly for large and complex models. Fast, state-of-the-art GWN approaches leverage a spatial index to approximate the GWN, typically coupled with a Taylor expansion which approximates the GWN contribution for far clusters of geometric primitives. However, such methods operate only on discrete inputs such as triangle meshes and point clouds, and would introduce containment errors near boundaries if applied to curved input. We extend support for fast GWN evaluation over arbitrary collections of NURBS curves in 2D and trimmed NURBS patches in 3D via a Bounding Volume Hierarchy that stores efficiently precomputed moment data in the hierarchy nodes. When querying the hierarchy, approximations for far clusters are used alongside direct evaluation for nearby NURBS primitives, achieving sub-linear complexity while preserving the geometric features in the vicinity of the query point. Central to our performance improvements is an adaptive subdivision strategy for NURBS primitives during a preprocessing phase, creating better spatial partitions while retaining the same accuracy for containment decisions as a direct evaluation. We demonstrate the performance and accuracy of our approach across a large collection of 2D and 3D datasets.

Computer science↗

DOE OSTI2024

Characterizing and improving the performance of molten-salt-steam heat exchangers in concentrating solar power plants

Shell-and-tube heat exchangers (HXs) for steam generation from molten salts in concentrating solar power (CSP) plants experience thermal fatigue due to significant temperature gradients and inherent transient operation. Molten salt-steam HX design lifespans exceed actual lifespans, and, as a consequence, designers overpredict plant profitability and operators neglect appropriate prescriptions to optimize these lifetimes. Here, this study refines HX lifespan estimates with data benchmarked against thermal-fluid mechanical modeling of stress and accumulated fatigue. Reduced-order thermal models of the molten salt-steam, shell-and-tube evaporator and superheater predict transient temperature profiles along the two HXs salt-steam flow paths. The modeled evaporator and superheater temperature profiles enable assessment of cyclic stresses within the HX tubesheets, where molten-salt HX failures are most common. Evaporator and superheater performance data from a current 110 MW elec commercial CSP plant provide a basis for validating the reduced-order HX models. HX life predictions derived from stochastic failure distributions serve as inputs for simulating and optimizing existing plant operations. The impact of the updated lifespans on overall plant revenue depends on operating scenarios. This study suggests that typical ramping rates for a CSP plant with a high-temperature Rankine cycle result in an evaporator and superheater life of approximately 10 and 25 years, respectively, compared to the design target of 30 years. Reduced HX lifespans decrease operational plant revenue on average by 4.6-5.1%. Furthermore, there may be as many as four HX replacements over the 30-year lifetime of the plant; and, purchase agreement loss due to failure to meet contractual production requirements can have ramifications that include the risk of bankruptcy.

14 SOLAR ENERGY↗

DOE OSTI2021

Thermodynamic Analysis of Thermo-vacuum Clothes Drying Operation

Clothes drying accounts for a significant amount of energy consumed in residential and commercial sectors. A thermal vacuum clothes drying technology (TVCD) is proposed as an advanced clothes dryer which can significantly reduce the energy requirements by expediting the drying process. In the conventional convective clothes dryer, hot dry air is introduced into the drum which gets in direct contact to dry the clothes. This process is energy inefficient since the significant amount of heat and the water carried out with the exhaust stream are wasted. In contrast to the conventional convective drying technique, the drying mechanism of TVCD is through nucleate boiling at low temperature due to reduced vessel pressure. The process is not only efficient but also reduces the required time for drying. The objective of this paper is to develop a comprehensive thermodynamic model to predict the transient drying process of TVCD. The three-stage system model including the detail analysis of individual components is capable of simulating the variation of the water content in the textile under various operational conditions. The preliminary results show that the drying time of 3 lb textile from 70% to 2.5% in TVCD is approximately four times less than the time required in the conventional clothes dryer. Parametric studies are carried out to understand the effect of operation conditions and component geometry on the system performance. Energy consumption of the system is also analyzed.

Yang, Cheng-Min↗