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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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Experimental and Numerical Study on the Effect of Nitric Oxide on Autoignition and Knock in a Direct-Injection Spark-Ignition Engine
We report Nitric Oxide (NO) can significantly influence the autoignition reactivity and this can affect knock limits in conventional stoichiometric SI engines. Previous studies also revealed that the role of NO changes with fuel type. Fuels with high RON (Research Octane Number) and high Octane Sensitivity (S = RON – MON (Motor Octane Number)) exhibited monotonically retarding knocklimited combustion phasing (KL-CA50) with increasing NO. In contrast, for a high-RON, low-S fuel, the addition of NO initially resulted in a strongly retarded KL-CA50 but beyond the certain amount of NO, KL-CA50 advanced again. The current study focuses on same high-RON, low-S Alkylate fuel to better understand the mechanisms responsible for the reversal in the effect of NO on KLCA50 beyond a certain amount of NO. Experiments were conducted to measure the responses of KL-CA50 and trace-autoignition CA50, the latter being indicative of CA50 at which end-gas autoignition starts to become measurable from the apparent heat-release rate. Chemical-kinetics simulations were conducted to reveal the role of NO for end-gas autoignition, with a specific focus on sequential autoignition in a thermally stratified end-gas. The simulation results reveal that the magnitude of low-temperature heat release (LTHR) generally increases with NO. However, the relative importance of NO for enhancing LTHR diminishes when the LTHR inherent to a fuel’s chemistry is strong, such as at lower temperatures in a thermal boundary layer. This rendered more uniform LTHR within a hypothetical thermal boundary and led to a more sequential (i.e. slower) autoignition event. It was also revealed that a change in compression ratio influences the importance of intermediate-temperature heat release (ITHR) due to changes of the temperature-pressure history of the end-gas. Together with the condition where end-gas autoignition occurs more sequentially, the shorter time spent in LTHR and ITHR regime can counter the increase in autoignition reactivity at high NO levels and allow KLCA50 to advance
THE APPLICATION OF SHORT-DURATION TECHNIQUES TO THE EXPERIMENTAL STUDY OF BASE HEATING. PART I- HIGH-ALTITUDE TESTING TECHNIQUE AND EXPERIMENTAL RESULTS FOR A 4-ENGINE ROCKET CONFIGURATION
High altitude base heating of 4-engine rocket nozzle configuration
Experimental Animal Decompressions to a Near-vacuum Environment. Experimental Animal Decompressions to Less than 2 Mm. Hg Absolute /pathologic Effects/
Times of consciousness, collapse, and survival and pathology examinations of dogs rapidly decompressed to near vacuum environment
Concepts for a theoretical and experimental study of lifting rotor random loads and vibrations. Phase 5C: Development of experimental methods
Test equipment which was built and the calibration tests are described. The test equipment consists of a two-bladed rotor of 16-in. diameter, the blades of which are elastically hinged in flapping. The feathering shaft of the blades can be harmonically rotated with the help of a cam mechanism located inside the hollow rotor shaft. The frequency range measured in the rotating system can be adjusted between 0 and 80 cps and the rotor speed between 0 and 40 cps. The test equipment is for measuring the flapping response of the blades to harmonic feathering excitation.
Subscale, hydrogen-burning, airframe-integrated-scramjet: Experimental and theoretical evaluation of a water cooled strut airframe-integrated-scramjet: Experimental leading edge
A water-cooled leading-edge design for an engine/airframe integrated scramjet model strut leading edge was evaluated. The cooling design employs a copper cooling tube brazed just downstream of the leading edge of a wedge-shaped strut which is constructed of oxygen-free copper. The survival of the strut leading edge during a series of tests at stagnation point heating rates confirms the practicality of the cooling design. A finite difference thermal model of the strut was also proven valid by the reasonable agreement of calculated and measured values of surface temperature and cooling-water heat transfer.
Experimental research on electric propulsion. Note 5: Experimental study of a magnetic field stabilized arc-jet
The possibility of using an electric arc under the influence of a magnetic field in ambient air to transform the heat energy of the working fluid arc into the kinetic energy of the jet was investigated. A convergent-divergent type nozzle was used. Variation of specific thrust and chamber pressure are discussed. Nitrogen was the propellant used.
Shuttle Experimental Radar for Geological Exploration (SERGE) project: Field work relating to the Shuttle Experimental Radar A (SIR-A) in Brazil (phase 2)
The ground observations undertaken over the northern position of Minas Gerais State, and part of Distrito Federal from 7 to 12 December 1982, along the Space Shuttle 2 flying orbit 22 of November 1981 are described. Field data related mostly with lithology, geological structures and forest cover, and specific geomorphological and pedological aspects were collected. Ground data are applied to evaluate the SIR-A Experiment, developed in the Space Shuttle-2 mission for natural resources mapping and prospecting.
Performance of Experimental Turbojet-engine Combustor I : Performance of a One-eighth Segment of an Experimental Turbojet-engine Combustor
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Experimental Performance Evaluation of a Hyper-Branched Polymer Electrolyte for Rechargeable Li-Air Batteries
A hyper-branched polymer (HBP) electrolyte is synthesized for rechargeable lithium-air (Li-air) battery cell and experimentally evaluated its performance in actual battery cell environment. Several real-world battery cells were fabricated with synthesized HBP electrolyte, pure lithium metal as anode and an oxygen permeable air cathode to evaluate reproducibility of the rechargeable Li-air battery cell. The effect of various conditions such as various HBP based electrolytes, discharge current -0.1~0.5 mA, cathode preparation processes and carbon contents on the battery cell performance were experimentally evaluated using the fabricated battery cells under dry air condition. Detailed HBP electrolyte synthesis procedures and experimental performance evaluation of Li-air battery cell for various conditions are presented. The experimental results showed that different conditions and processes significantly affect the Li-air battery performance. Upon taking into account the effect of different conditions and processes, optimized HBP electrolyte materials, cathode process and conditions were determined. Several Li-air battery cells were fabricated with optimized conditions and optimized battery cell materials to determine the reproducibility and performance consistency. Experimental results showed that over 55–65 h of discharge occurred over 2.5 V terminal cell voltage with all three optimized Li-air battery cells. It implied that the optimized Li-air battery cells were reproducible and were able to hold charge over 2.5 V for more than 2 days. Experimental results of the Li-air battery cell with further refined optimized materials revealed that the battery cell can discharge more than 10 days (i.e., more than 250 h) at or above 2.0 V. The experimental results also showed that the Li-air battery discharge time got shorter as the discharge-charge cycle increases due to increase in internal resistances of battery cell materials. The experimental results confirmed that the lithium-air battery cell can be reproduced without loss of performance and can hold charge more than 10 days at or over 2.0 V. The investigation results obtained may usher a pathway to manufacture a long-life rechargeable Li-air battery cell in the near future.
A combined experimental and computational analysis of failure mechanisms in open-hole cross-ply laminates under flexural loading
In this work, integrated experimental tests and computational modeling are proposed to investigate the failure mechanisms of open-hole cross-ply carbon fiber reinforced polymer (CFRP) laminated composites. In particular, we propose two effective methods, which include width-tapered double cantilever beam (WTDCB) and fixed-ratio mixed-mode end load split (FRMMELS) tests, to obtain the experimental data more reliably. We then calibrate the traction-separation laws of cohesive zone model (CZM) used among laminas of the composites by leveraging these two methods. The experimental results of fracture energy, i.e. G Ic and G Tc , obtained from WTDCB and FRMMELS tests are generally insensitive to the crack length thus requiring no effort to accurately measure the crack tip. Moreover, FRMMELS sample contains a fixed mixed-mode ratio of G IIc /G Tc depending on the width taper ratio. Examining comparisons between experimental results of FRMMELS tests and failure surface of B–K failure criterion predicted from a curve fitting, good agreement between the predictions and experimental data has been found, indicating that FRMMELS tests are an effective method to determine mixed-mode fracture criterion. In addition, a coupled experimental-computational modeling of WTDCB, edge notched flexure, and FRMMELS tests are adopted to calibrate and validate the interfacial strengths. Finally, failure mechanisms of open-hole cross-ply CFRP laminates under flexural loading have been studied systematically using experimental and multi-scale computational analyses based on the developed CZM model. The initiation and propagation of delamination, the failure of laminated layers as well as load-displacement curves predicted from computational analyses are in good agreement with what we have observed experimentally.
Validation and Verification for INL Modelica-based TEDS models Via Experimental Results
This report provides an overview on the verification and validation (V&V) of the Thermal Energy Distribution System (TEDS) model developed in the Modelica process modeling ecosystem using experimental data. Model development has led to the creation of a dynamic process model of the experimental TEDS facility housed within the Energy Systems Laboratory (ESL) at Idaho National Laboratory (INL). The model was then used during the preconstruction phase of the experimental effort to inform experimental design (e.g., insulation requirements, bypass line placement, expected performance of components) and to test innovative control schemes prior to the initial operation. The TEDS model developed in Modelica includes the primary components of the TEDS experimental unit: a 200kW Chromalox heater; a single-tank packed-bed thermal energy storage system filled with 0.125-inch alumina (Al2O3) beads; an ethylene-glycol-to-Therminol-66 heat exchanger; system piping; five control valves; and all associated temperature, pressure, and volumetric flow sensors. Using the Institute of Electrical and Electronics Engineers (IEEE) V&V methodologies, considered the gold standard in the engineering field, the model was verified using a combination of static analysis, spatial convergence, and regression tests. Then using dynamic time warping (DTW) initial runs to validate and tune the TEDS model versus the experiment were conducted. This tuning method was accomplished using the INL Risk Analysis Virtual ENvironment (RAVEN) software package. Tuning is required to account for physical phenomena that are less understood within the empirical heat transfer correlations. Through the commencement of this work, a systems-level model of TEDS with associated control systems, sensors, piping diameters, and component capabilities has been created. This model was utilized in the pre-experimental phase to inform system design, insulation thicknesses, and potential control schemes to operate the system effectively and safely. Then, initial experimental startup and operational data were used to demonstrate the validation and tuning methodology. This process demonstrates the classical two-step approach of a model informing experimental design followed by the experiment validation and tuning the model.
Practical Insights on Applying Simulation-Based Control Methods in Experimental Studies
Advanced nuclear reactors are crucial to the future of energy both in the United States and around the globe. In contrast to the current operating fleet, they are characterized as being deployable in remote locations and able to operate in semi-autonomous or autonomous fashion. This leap forward necessitates a new reactor control paradigm. Because advanced nuclear reactors are still under development in the United States, the creation of new control methods to achieve autonomous operations has been based on systems modeling and simulation. However, an important factor in successfully deploying these new control methods is the ability to seamlessly transition from simulation environments to real-world settings. Control methods tested in both simulation and experimental settings need to be investigated in the context of advanced reactor applications. This work developed a series of simple controllers for Idaho National Laboratory (INL)’s Microreactor Applications Research Validation and Evaluation (MARVEL) microreactor operating in load-following scenarios. These controllers were tested in both simulation and experimental settings, and a comparative performance analysis was performed. The simulation tests leveraged the Control and Optimization Modular Modeling Application for Nuclear Deployment (COMMAND) software developed in a previous stage of the current effort, along with the MARVEL Reactor Excursion and Leak Analysis Program (RELAP5-3D) and Monte Carlo N-Particle (MCNP) models. The experimental tests leveraged the COMMAND software, MARVEL models, and the U.S. Department of Energy Microreactor Program’s Microreactor Automated Control System (MACS). MACS was developed to serve as a control method testbed. It was customized to mirror the MARVEL microreactor, and COMMAND enabled MACS to emulate the physics of MARVEL. The load-following controller was developed using the simulation platform, with efforts to emulate real systems by introducing actuator saturation and noise. These factors were incrementally accounted for in the controller design. After finalizing the controller design, it was implemented with the experimental setup. The experimental conditions tested included an initial test under conditions similar to the final simulation test, and two additional scenarios. The first scenario introduced additional actuator saturation to account for equipment aging over time, which was unknown to the controller. The second scenario introduced sensor delay, a phenomenon anticipated with the use of remote operations or wireless communication in advanced reactors. These tests revealed several notable differences. While the controller performed well in simulation, it exhibited several limitations when transitioning to hardware. The main challenges involved maintaining the steady-state target power, as evidenced by larger error values between the true reactor power and setpoint power, as well as persistent oscillations in controlled reactor power. These issues could lead to unacceptable transient conditions in real reactor testing. Introducing actuator aging and stochastic delays in the experimental setup significantly impacted controller performance, resulting in increased overshoot and undershoot, and exacerbated error and oscillations previously mentioned. These findings underscore the importance of experimental testbeds for testing and validating control methods, as controllers developed using only theory and/or simulation may perform unexpectedly when applied to actual hardware. This research emphasizes the need for an experimental testbed for achieving such validation.
Optimal Experimental Design With Fast Neural Network Surrogate Models
Designing optimal experiments minimizes the uncertainty of results and maximizes the efficient use of resources. Herein, machine learning surrogate models and the approximate coordinate exchange (ACE) algorithm are used to determine optimum experimental designs over large or arbitrarily restrictive design spaces. Optimal experimental design is particularly salient in materials science where experiments are expensive and material properties must often be inferred indirectly. The proposed framework is demonstrated by finding optimal experiments with which the hidden constituent properties of composite materials can be most efficiently inferred from observable experimental outcomes. The optimum experimental design is given by an information-theoretic criteria, which maximizes the conditional mutual information between the hidden properties and the expected experimental outcomes. To perform tractable optimization a neural network is trained as a surrogate model to mimic a physics based simulation, which can calculate the expected experimental outcome based on a candidate experimental design and sampled constituent properties. The ACE algorithm is used to optimize over large design spaces with many tests and controlled parameters where an exhaustive search would be intractable even with the surrogate model. Using this approach, optimal experimental designs that are consistent with those produced by heuristic knowledge and established best practices are found; then optimal designs in larger design spaces where heuristic knowledge is unavailable are examined.
High salinity seawater boiling point elevation: Experimental verification
Boiling point elevation (BPE) for high salinity solutions is a crucial parameter that significantly affects the overall thermal efficiency of desalination, water treatment, and many other industrial processing systems, especially when minimum or zero liquid discharge is a key requirement. This paper addresses the discrepancies among the empirical correlations reported in the literature that were commonly used to determine BPE for seawater solutions. An evaluation of the experimental data with low solution concentration reveals that the data cannot be extrapolated to determine the BPE at high concentration (X > 140 ppt or g/kg). Besides, disparities are established within different equations used to determine the BPE for high salinity seawater. As a result of the minimal availability of experimental data of BPE for X > 140 ppt and the need to eliminate the discrepancies, an experimental setup was built, which can produce reliable and repeatable BPE data for any solution concentration. Boiling points were obtained experimentally for seawater solutions with a wide range of salinity (X between 20 and 280 ppt) and brine solution temperature (t b between 20 and 80°C). The experimental results of boiling point elevations for seawater are further compared with the experimental data and analytical results reported in the literature. The newly obtained experimental results show that the minimum and maximum BPE values for the brine solutions tested are 0.175°C at t b = 80°C and X = 20 ppt, and 11.6°C at t b = 80°C and X = 280 ppt, respectively. Furthermore, the measured BPE data for seawater concentration over 80 ppt are fitted and presented using an appropriate fitting model. The new correlation can accurately predict the BPE for high salinity seawater brines and thus should be very helpful in the design of high-energy-efficient evaporation systems.
Foundations of Rigorous Cyber Experimentation
This report presents the results of the “Foundations of Rigorous Cyber Experimentation” (FORCE) Laboratory Directed Research and Development (LDRD) project. This project is a companion project to the “Science and Engineering of Cyber security through Uncertainty quantification and Rigorous Experimentation” (SECURE) Grand Challenge LDRD project. This project leverages the offline, controlled nature of cyber experimentation technologies in general, and emulation testbeds in particular, to assess how uncertainties in network conditions affect uncertainties in key metrics. We conduct extensive experimentation using a Firewheel emulation-based cyber testbed model of Invisible Internet Project (I2P) networks to understand a de-anonymization attack formerly presented in the literature. Our goals in this analysis are to see if we can leverage emulation testbeds to produce reliably repeatable experimental networks at scale, identify significant parameters influencing experimental results, replicate the previous results, quantify uncertainty associated with the predictions, and apply multi-fidelity techniques to forecast results to real-world network scales. The I2P networks we study are up to three orders of magnitude larger than the networks studied in SECURE and presented additional challenges to identify significant parameters. The key contributions of this project are the application of SECURE techniques such as UQ to a scenario of interest and scaling the SECURE techniques to larger network sizes. This report describes the experimental methods and results of these studies in more detail. In addition, the process of constructing these large-scale experiments tested the limits of the Firewheel emulation-based technologies. Therefore, another contribution of this work is that it informed the Firewheel developers of scaling limitations, which were subsequently corrected.
Toward a Seamless Integration of Computing, Experimental, and Observational Science Facilities: A Blueprint to Accelerate Discovery
The Department of Energy, Office of Science operates world-leading facilities for experimental, observational, and computational science. DOE supercomputing facilities will reach performance at the scale of ExaFLOPs in the coming years, enabling new vistas of scale and precision for large scale simulations and data analysis. Experimental scientific facilities are undergoing similar upgrades that will lead to higher data rates and correspondingly larger computational demands, and will increase the need for near-real-time processing and resilient support for more complex workflows. A transformation of science is underway, with workloads at supercomputing facilities increasingly driven by this explosion of data from instruments and experimental facilities, as well as the accelerating use of Artificial Intelligence (AI) as a tool for scientific discovery. A seamless integration of computing, networking, instruments, and experimental facilities is required to support these emerging workloads and open up a new frontier of U.S. leadership in scientific discovery. We propose to accomplish this by providing frictionless access to the ASCR supercomputing facilities. We describe our vision of combining the power of ASCR supercomputers and networking infrastructure into an integrated scalable fabric, available to end user scientists via interfaces that aim to automate and simplify access to high performance computing systems. This will enable unprecedented computational science capabilities for experimental and observational facilities, and will create new opportunities to combine large simulations and modeling with experimental facility data analysis. This blueprint for creating an integrated network of computational and experimental facilities will provide an enriched discovery environment and open doors for new scientific communities to access the DOE’s world-leading computing and networking capabilities.
Cold air study of the effect on turbine stator blade aerodynamic performance of coolant ejection from various trailing edge slot geometries. 2: Comparison of experimental and analytical results
Experimentally determined efficiencies of turbine stator blades having trailing-edge coolant ejection are compared with efficiencies predicted from two previously published approximate analytical methods. The experimental results were obtained from two-dimensional data with the temperature of the primary and coolant flows both being nearly ambient. Data from five stator blade configurations having different slotted trailing-edge geometries were included in the comparison. The two analytical methods gave results which agreed reasonably well with experimental results. An average of the absolute values of differences between experimental and predicted efficiencies for all five blade configurations showed that one method gave average efficiency differences which were about 1.3 percent different than experimental efficiencies, while the other method gave average efficiency differences that were about 0.7 percent different than experimental. However, in some instances, maximum differences of as much as 4 percent occurred. A comparison between experimental and analytical results indicated that the ratio of trailing-edge slot width to trailing-edge thickness influences the measured efficiencies to a greater extent than is accounted for by either analytical model.