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At least 505 records · Page 28
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

On the Performance of Detecting Injection of Fabricated Messages into the CAN Bus

There have been several public demonstrations of attacks on connected vehicles showing the ability of an attacker to take control of a targeted vehicle by injecting messages into their Controller Area Network (CAN) bus. In this article, using injected speed reading and Revolutions Per Minute (RPM) reading messages in in-motion vehicle, we examine the ability of the Pearson correlation and the unsupervised learning methods k-means clustering and Hidden Markov Model (HMM) to differentiate ’no-attack’ and ’under-attack’ states of the given vehicle. We found that the Pearson correlation distinguishes the two states, the k-means clustering method has an acceptable accuracy but high false positive rate and HMM detects attacks with acceptable detection rate but has a high false positive in detecting attacks from speed readings when there is no attack. The accuracy of these unsupervised learning methods are comparable to the ones of the supervised learning methods used by CAN bus Intrusion Detection System (IDS) suppliers. In addition, the article shows that studying CAN anomaly detection techniques using off-vehicle test facilities may not properly evaluate the performance of the detection techniques. Finally, the results suggest using other features besides the data content of the CAN messages and integrate knowledge about how the Electronic Control Units (ECUs) collaborate in building effective techniques for the detection of injection of fabricated message attacks.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Experimental, numerical and analytical evaluation of j × B -thrust for fast-liquid-metal-flow divertor systems of nuclear fusion devices

Abstract Divertor systems of fusion devices are exposed to intense heat loads from plasmas, which degrade solid plasma-facing components. Fast liquid metal (LM) flow divertors may be more advantageous for this purpose but have risk of piling due to intense magnetohydrodynamic (MHD) drag. However, severe deceleration of the flow could be countered with the injection of currents that are transverse to external magnetic fields, allowing to thrust the flow with j × B (Lorentz) forces. Given that the injection of currents as an approach to propel LM-divertor flows has remained experimentally understudied, this article focuses on the evaluation of j × B -thrust and finding its drawbacks. j × B -thrust was experimentally tested with free-surface-LM flows, a vertical magnetic field and an externally applied current. Experiments were reviewed with a theoretical model, showing agreement in the trends of theory and experiments. Full 3D-MHD-free-surface-flow simulations were also performed with FreeMHD and confirmed the sensitivity to unstable flow behavior in LM systems when applying external currents. Furthermore, excessive power requirements are expected for the implementation of j × B -thrust at the reactor scale, making these systems inefficient for commercial devices. This paper evidences that the simple operation of a LM-flow divertor with j × B -thrust, without any of the instabilities caused from reactor plasmas or parasitic currents, already presents intrinsic challenges.

Magnetohydrodynamics↗
DOE OSTI2020

A Novel Active Optimization Approach for Rapid and Efficient Design Space Exploration Using Ensemble Machine Learning

In this work, a novel design optimization technique based on active learning, which involves dynamic exploration and exploitation of the design space of interest using an ensemble of machine learning algorithms, is presented. In this approach, a hybrid methodology incorporating an explorative weak learner (regularized basis function model) that fits high-level information about the response surface and an exploitative strong learner (based on committee machine) that fits finer details around promising regions identified by the weak learner is employed. For each design iteration, an aristocratic approach is used to select a set of nominees, where points that meet a threshold merit value as predicted by the weak learner are selected for evaluation. In addition to these points, the global optimum as predicted by the strong learner is also evaluated to enable rapid convergence to the actual global optimum once the most promising region has been identified by the optimizer. Additionally, this methodology is first tested by applying it to the optimization of a two-dimensional multi-modal surface and, subsequently, to a complex internal combustion (IC) engine combustion optimization case with nine control parameters related to fuel injection, initial thermodynamic conditions, and in-cylinder flow. It is found that the new approach significantly lowers the number of function evaluations that are needed to reach the optimum design configuration (by up to 80%) when compared to conventional optimization techniques, such as particle swarm and genetic algorithm-based optimization techniques.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Time-Based CAN Intrusion Detection Benchmark

Modern vehicles are complex cyber-physical systems made of hundreds of electronic control units (ECUs) that communicate over controller area networks (CANs). This inherited complexity has expanded the CAN attack surface by the injection of malicious messages that vary their time-based characteristics. To detect these malicious messages, time-based intrusion detection systems (IDS) have been proposed. However, time-based IDS are usually trained and tested on low-fidelity datasets with unrealistic labeled attacks. This makes difficult the task of evaluating, comparing, and validating IDS. Here we detail and benchmark four time-based IDS in a dataset with real and advanced attacks. We found that methods with strong assumptions regarding the distribution of inter-arrival times have lower performance than distribution agnostic based methods. In particular, distribution agnostic based methods outperform distribution based methods at least on $55\%$ in area under the precision-recall (AUC-PR) curve. Our results expand the body of knowledge of CAN time-based IDS by providing details of these methods and reporting their results when tested on datasets with real and advanced attacks. We describe limitations, open challenges, and how lessons learnt from this research can inform the design of deployable time-based IDS in modern vehicles.

Blevins, Deborah↗
DOE OSTI2022

Foam Fracturing Study for Stimulation Development of Enhanced Geothermal Systems

The large thermal gradients and high subsurface temperatures of the western region of the U.S. hold great potential for the implementation of enhanced geothermal systems (EGS). The development of these potential EGS resources requires stimulation of the reservoir to enhance permeability and it has been widely reported that a substantial amount of water will be required should conventional hydraulic stimulation be used. This presents a huge challenge and a high risk to the geothermal development because the water stress1 in these areas is already high or extremely high. The use of foam, a gas/liquid mixture predominantly composed of gas, in fracturing is considered and explored in this project as a potential approach to address water concerns with hydraulic stimulation in the development of EGS. This project, led by Oak Ridge National Laboratory (ORNL) in collaboration with Temple University, was awarded in an open lab call in 2018, and was part of the DOE GTO waterless stimulation initiative. The goal of the project was to demonstrate the feasibility of foam fracturing for EGS development through two primary tasks: Task 1: Laboratory study of the effectiveness of foam fracturing for representative geological materials, including cyclic pressurization using foam (led by ORNL) and Task 2: High temperature foam material selection and characterization (led by Temple University). In FY19, ORNL finished the critical review on serval issues associated with foam fracturing and the implementation of the proposed tasks in a lab study (Wang, et al., 2019), and completed the foam fracturing testing using cement as a model material (Wang, et al, 2020a). The work at ORNL was geared up to develop a brand-new foam testing system in FY20. The purchase of main components for the new system was finished in the first half of the FY20. The assembly of the foam testing system and foam fracturing testing were completed in the second half of the FY20 (Wang, et al., 2021a). Task 1 required the development of a test system which can be used to perform hydraulic fracturing of geological specimens with both water and foamed liquids at pressure up to 6,000 psi (41.4 MPa). The system possesses several capabilities that conventional injection systems lack for hydraulic fracturing. In addition to its ability to generate foam with controlled quality, it is capable of cycling pressure levels between specified values up to frequencies of 50 Hz. The latter capability was developed to evaluate the hypothesis that cyclic loading of samples would produce enhanced fracturing. The system consists of two sections: one for foam generation and another for foam injection. The foam is generated through separate control and pressurization of liquid and gas phases with controlled flow rates. The injection section is equipped with a low-flow Coriolis flow that monitors the density of foam to ensure the injection is in the range of target foam quality2. Experimental results of foam fracturing are reported for cylindrical granite specimens using water and aqueous N2 foam as the fracturing fluids. All experiments were performed for unconfined conditions. The effects of injection mode (i.e., monotonic vs cyclic pressurization) on breakdown pressure and failure response sample were investigated using water alone as a fracturing fluid and foams with a range of compositions. It was found that in the case of monotonic injection, the breakdown pressure of granite specimens tended to be slightly higher when fracturing with foam. Additionally, with a foam quality of 90%, the water use can be reduced by 50 to 84%, depending on hole size. On the other hand, it was observed that the breakdown pressure can be brought down to 70% of the monotonic breakdown pressure by using low cycle fatigue. Finally, discussions are presented regarding injectivity and water use reduction.

15 GEOTHERMAL ENERGY↗
DOE OSTI2023

Particle Flow Distribution in a Fluidized-Particles Multitube Solar Receiver

A fluidized-particles two-tube solar receiver was tested at ambient temperature at PROMES Laboratory to investigate the influence of an inhomogeneous solar flux density on the particle mass flow rate between the tubes. The principle of this 3rd generation solar receiver is to fluidize the particles in a container, called dispenser, in which the tubes’ bottom are immersed. The fluidized particles are flowing upward the tubes by applying an overpressure in the dispenser. Air velocities are changed inside the tubes, thanks to air mass flow controllers, to represent temperature heterogeneity between the tubes. Air velocities from 0.05 up to 0.52 m/s were tested, both in homogeneous and heterogeneous conditions. In the heterogeneous ones, the differences in air velocity between the tubes aim to mimic a difference in temperature from 20 to 100 % with homogeneous air flow rates injected. The following conclusions were drawn. First, the particle mass flux in the tubes are the same with homogeneous air velocities, each one following a calibration map previously obtained. Second, different air velocities lead to different particle mass flux. Third, the rise of the total particle mass flux diminishes the pressure in the dispenser. Four, this diminution of pressure leads to a decrease of the particle mass flow rate of the tube with the lower air velocity. This influence can lead in some cases to the stop of the fluidized bed circulation in the affected tube.

Sahuquet, Guillaume (ORCID:0000000302752890)↗
DOE OSTI2020

Slip Tendency Analysis of Fracture Networks to Determine Suitability of Candidate Testbeds for the EGS Collab Hydroshear Experiment

Experiment 2 of the EGS Collab project is aimed at testing stimulation by hydro-shearing of existing natural fractures, versus Experiment 1, which is focused on hydraulic fracturing a rock mass to enhance permeability. The main criterion for the testbed selection in Experiment 2 is the presence of an interconnected network of fractures, at least 10 meters in extent, and with orientations such that shear slip can be induced at injection pressures less than the minimum horizontal stress (Shmin). The feasibility analysis for this experiment requires a well-constrained stress state along with well-characterized fracture networks. The fracture systems at two candidate locations in the Sanford Underground Research Facility (SURF), the 4850 Level (number refers to depth below ground surface in feet) and the 4100 Level, have been characterized to different extents. The 4850 Level has a well-characterized Discrete Fracture Network (DFN) from borehole (drilled for an experimental test bed) and drift observations. In contrast, the 4100 level has a fracture network characterized only by observations from the drift wall, which provides little constraint on fracture extents. This paper will present assessments for the interpreted slip potential for the natural fractures at the two locations. Data uncertainties are addressed by performing a probabilistic analysis that takes into account the uncertainty in the stress state, uncertainty in the fracture properties, and preliminary borehole locations. There is strong evidence of shear stimulation of some natural fractures in Experiment 1 on the 4850 level. We use examples of natural fractures strongly linked to shear stimulation in Experiment 1 from multiple monitoring indicators to test the consistency of the stress model and guide the uncertainty interpretation. This analysis is intended to guide the site selection process for Experiment 2 by highlighting the fracture orientations that are likely to be shear-stimulated in a majority of modeled realizations.

40 EE - Geothermal Technologies Office (EE-4G)↗
DOE OSTI2022

Effects-Based Monitoring of Geomagnetically-Induced Current Using a Convolutional Neural Network

Geomagnetically-induced current (GIC) due to space weather can flow in the power grid causing undesirable effects such as transformer overheating, misoperation of protection devices, and potential blackouts. It is therefore important to monitor GIC in the power grid to improve online situational awareness and decision-making of system operators during a geomagnetic disturbance. To avoid the costly installation of GIC monitors at transformers’ neutrals, it is desirable to find correlations between GIC and already-monitored parameters. Hence, this work proposed the use of a convolutional neural network (CNN) to compute GIC amplitudes from learned patterns in the time-series data of transformer even harmonic currents. Using an electromagnetic transient program, GIC injection simulations were performed for a modeled Dominion Energy Virginia (DEV) substation with two 504 MVA, 500/230 kV transformers. Data collected from these offline simulations were used to train the CNN to provide online GIC monitoring. Testing the CNN performance involved using real GIC measurements from published literature and from a physical GIC monitor in the DEV area. Finally, the results showed that the proposed method was able to provide GIC readings with a root mean squared error of 1.56 A/phase (equivalent to an average accuracy of 94%) for these real GIC waveforms.

42 ENGINEERING↗
DOE OSTI2022

A Qualitative Strategy for Fusion of Physics into Empirical Models for Process Anomaly Detection

To facilitate the automated online monitoring of power plants, a systematic and qualitative strategy for anomaly detection is presented. This strategy is essential to provide credible reasoning on why and when an empirical versus hybrid (i.e., physics-supported) approach should be used and to determine the ideal mix of these two approaches for a defined anomaly detection scope. Empirical methods are usually based on pattern, statistical, and causal inference. Hybrid methods include the use of physics models to train and test data methods, reduce data dimensionality, reduce data-model complexity, augment data, and reduce empirical uncertainty; hybrid methods also include the use of data to tune physics models. The presented strategy is driven by key decision points related to data relevance, simple modeling feasibility, data inference, physics-modeling value, data dimensionality, physics knowledge, method of validation, performance, data availability, and suitability for training and testing, cause-effect, entropy inference, and model fitting. The strategy is demonstrated through a pilot use case for the application of anomaly detection to capture a valve packing leak at the high-pressure coolant injection system of a nuclear power plant.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Quarterly Research Performance Progress Report (Q8)

As part of Task 1, we have started by testing our modeling capabilities by reproducing isothermal DFIT simulations presented in the literature. Once satisfied with the results we have started by targeting the modeling of the DFITs at conducted at well 58-32. We have a identified a specific test (cycle 4 in zone 2) as the most interesting to be model with GEOS hydraulic fracturing module. Thus, we have first produced results with an isothermal model and adjusted model parameters to get a satisfying match with field pressure data. The, we have added thermal effects and compared the modeling results with and without thermal effects to estimate how thermal effects may influence test interpretation. Models seem to suggest that, for small volumes of fluid, thermal effects are moderate. In Task 2, we have adapted GEOS phase-field formulation to be able to simulate near-wellbore hydraulic fracture nucleation and propagation. We have devised a novel formulation that, compared to other existing ones, incorporates rock strengths. We have submitted a journal publication about our work. We are currently employing this phase-field formulation to model the experiments taking place at U Pitt and help us understand the effect of various parameters. In Task 3, we have built a model of the region surround well 16A and have started modeling stage 3 stimulation because of its simpler planar geometry. After calibrating simulation parameters using known analytical solutions, we have simulated the stage 3 stimulation using our isothermal hydraulic fracturing module, varying the permeability field, the stress conditions including different physics to get a better understanding of the numerical challenges and of the effects of varying these parameters on the simulation results. In Task 4 laboratory experimentation, a set of specialized drilling and injection tools has been customized and constructed to accommodate an inclined well with an orientation of up to 30 degrees relative to material anisotropy or principal stress axes. These inclined samples have also undergone thermal stress and hydraulic fracturing at a temperature of 190 degrees Celsius. Furthermore, both vertical and deviated sampling testing setups enable an extended analysis of post-peak pressure behaviors, facilitating post-test pressure analyses such as the G-function, step rate, and fracture reopening measurements. Thus, the key components of in-situ stress estimation can be extracted and validated through our experiment, providing a solid foundation for validating existing in-situ stress estimation theories or proposing new ones. Simultaneously, we are integrating computer vision techniques with traditional experimental fracture observation methods such as multi-overcore/slicing and water-penetration fracture observation. This combination will prove beneficial in populating the hydraulic fracture patterns database, generated under challenging EGS conditions. This approach aims to deepen our understanding of the complexities in EGS reservoirs and pave the way for future data-driven investigations. Additionally, PITT has also equipped the ELE International compression machine, which is now prepared for conducting indirect tensile and fracture toughness tests. These tests will aid in characterizing how rock fabrics influence the resulting fracture patterns. Additionally, we have completed the required personnel training and gained access to Scanning Electron Microscopy (SEM) and Energy Dispersive Spectroscopy (EDS) for conducting more detailed characterization and analysis of rock fabrics, as well as the examination of thermal and hydraulically induced fracture patterns. Thus, the PITT team has effectively demonstrated the capabilities of our experimental apparatuses in exploring the thermal effects, well deviation angles, material anisotropy, and operational choices (such as circulation rate, injection fluid viscosity, and injection rate) and their impact on pressure responses and fracture trajectories under the Utah FORGE conditions.

15 GEOTHERMAL ENERGY↗
DOE OSTI2022

Technology Enablers for Advanced Gasoline Compression Ignition Engines

To meet current emission regulations and increasingly demanding global fleet CO2 standards on fuel economy and future trends towards life cycle GHG emissions, advanced combustion engines remain significant in the passenger vehicle sector to achieve high efficiency and low emissions over the full operating range. Lean burn gasoline compression ignition (GCI) technology has shown to have the most potential in reaching these goals, although it faces challenges in the operating range. In this study, an advanced GCI engine is considered with the capability to operate under two combustion modes, namely low temperature combustion (LTC) and GCI. They are enabled with the use of two Hyundai in-house developed technologies; an advanced valve control mechanism known as continuously variable valve duration (CVVD) and a high-pressure gasoline injection system. At low load, the engine utilizes dual CVVD and dual CVVT (continuously variable valve timing) mechanisms for both intake and exhaust valvetrains to enable NVO (negative valve overlap) to trap hot residuals. The hot residuals enable low load auto-ignition, and the phasing control of that auto-ignition is achieved by varying the degrees of NVO, and in turn, the amount of hot residuals. This is done in real time with respect to the changes in engine loads or operating conditions, significantly improving cylinder-phasing control in LTC mode, and subsequently is able to realize a fuel economy gain and reduced emission benefits. Early direct injection during NVO or intake stroke is used to form homogenous or quasi-homogenous air-fuel mixture for LTC. At mid to high loads, late direct injection of gasoline or GCI mode is employed to take advantage of the high volatility and high resistance to auto-ignition of gasoline fuel, so that diesel-engine like high combustion efficiency can be achieved with lower soot emissions for the same NOx level as diesel combustion. In this paper, the key control and fueling technologies that enable this multiple mode combustion are introduced, and the resultant analysis on engine test and CFD simulation at LTC and GCI operating conditions are presented in detail.

Gasoline compression ignition, low temperature com↗
DOE OSTI2025

Development of Hydrogen Burner for FT4000® Aeroderivative Engine - Final Report

This report details an effort to develop a retrofittable fuel/air injector for the FT4000® aeroderivative gas turbine that enables use of hydrogen as a carbon-free fuel for efficient power generation. The FT4000 engine’s low-NOx combustor was developed by Pratt & Whitney and RTX Technology Research Center with core technology from the Pratt & Whitney PW4000 turbofan aircraft engine. The current FT4000 production engine operates on either natural gas or No. 2 fuel oil with water injection to achieve high thermal efficiency and low emissions. This engine is fielded by Mitsubishi Power Aero and delivers 70 MW of power with a simple-cycle efficiency of over 41% when operating with wet compression. The work reported here advances the technology readiness level of the FT4000 combustor for operation with hydrogen, starting with an experimental assessment of the current production hardware with increasing hydrogen content mixed with natural gas and ending with improved nozzle concepts for fully robust operation with 100% hydrogen. High-pressure single-sector combustor rig tests have been completed, demonstrating the ability for the dual fuel nozzle to operate an FT4000 combustor on 100% hydrogen with low nitrogen oxide (NOx) emissions. Metal temperature measurements and video images of the flame structure from zero to 100% hydrogen highlight opportunities to improve the fuel nozzle robustness for high hydrogen conditions. The design of new fuel/air mixer concepts to improve durability and operability with high hydrogen levels was also completed. A total of eleven new concepts were developed and analyzed, ranging from modifications to the bill-of-materials nozzle to fully clean sheet designs. The concepts were evaluated with non-reacting and reacting flow evaluations to assess the performance of the new hardware designs. Non-reacting tests included Phase Doppler Particle Analysis (PDPA) for droplet size and velocity, mechanical patternation for liquid water flux, and planar laser induced fluorescence (PLIF) with acetone-seeding for gaseous fuel/air mixing characterization. Five scaled candidate fuel nozzle designs, in addition to a scaled bill-of-materials nozzle, were then successfully evaluated in an atmospheric pressure burner rig. The nozzles were evaluated for performance with natural gas, hydrogen/natural gas blends, and pure hydrogen. For 100% hydrogen, the nozzles were evaluated with and without water injection. Optical and infrared imaging of the flame and fuel nozzle was captured. NOx emissions were sampled from fixed emissions probes. The results show measurable differences between the various designs, and the data was used to down-select the two most promising designs to advance to future full pressure rig testing. Results from this study have cleared the current production FT4000 engines with dual fuel nozzles to operate at baseload power on blends of hydrogen mixed with natural gas and water. Two promising nozzle designs have been developed to enable fully robust operation with up to 100% hydrogen. These nozzles require validation at full baseload operating conditions before they can be introduced to the field.

03 NATURAL GAS↗
DOE OSTI2023

First feedback-controlled divertor detachment in W7-X: Experience from TDU operation and prospects for operation with actively cooled divertor

In the last experimental campaign (OP1.2b) of the stellarator Wendelstein 7-X (W7-X), boronisation as a mean for first wall conditioning was applied for the first time which led to strongly reduced impurity fluxes from plasma-facing components. Thermal detachment at the uncooled target plates of the test divertor unit (TDU) was reached at higher plasma densities and was accompanied by high recycling of neutrals at the target plate. A feedback control system was established in W7-X to actively control the gas injection (actuator) for plasma fuelling and impurity seeding [3] through the divertors. It allowed very successful stabilisation of the detached plasma condition state as well as mitigation of thermal overloads to some baffle tiles. Different routinely available diagnostic signals were used as input parameters (sensors). We describe the setup of the feedback control system, its performance and provide some example results with the main focus on the development of the control scheme which led to the detachment stabilisation over the entire longest (30 s) high-power discharge at W7-X so far. In view of the achieved very successful detachment stabilisation and the necessity to include simultaneous optimisation of the core performance in the future, the feedback control system is being upgraded for the upcoming campaign (OP2.1) in which the water cooled and hereby inherently steady-state capable divertor has been currently installed. The prospects and some experiment ideas for active detachment control are discussed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Time-Based CAN IDS Paper Results Code

Modern vehicles are complex cyber-physical systems made of hundreds of electronic control units (ECUs) that communicate over controller area networks (CANs). This inherited complexity has expanded the CAN attack surface which is vulnerable to message injection attacks. These injections change the overall timing characteristics of messages on the bus, and thus, to detect these malicious messages, time-based intrusion detection systems (IDSs) have been proposed. However, time-based IDSs are usually trained and tested on low-fidelity datasets with unrealistic, labeled attacks. This makes difficult the task of evaluating, comparing, and validating IDSs. Here we detail and benchmark four time-based IDSs against the newly published ROAD dataset, the first open CAN IDS dataset with real (non-simulated) stealthy attacks with physically verified effects. We found that methods that perform hypothesis testing by explicitly estimating message timing distributions have lower performance than methods that seek anomalies in a distribution related statistic. In particular, these “distribution-agnostic” based methods outperform “distribution-based” methods by at least 55% in area under the precision-recall curve (AUC-PR). Our results expand the body of knowledge of CAN time-based IDSs by providing details of these methods and reporting their results when tested on datasets with real advanced attacks. Finally, we develop an after-market plug-in detector using lightweight hardware, which can be used to deploy the best performing IDS method on nearly any vehicle.

Moriano, Pablo [Oak Ridge National Lab. (ORNL), Oa↗
DOE OSTI2022

In Situ Plasma Processing of Superconducting Cavities at JLab

Jefferson Lab has an ongoing R&D program in plasma processing which is close to going into production pro-cessing in the CEBAF accelerator. Plasma processing is a common technique for removing hydrocarbons from surfaces, which increases the work function and reduces the secondary emission coefficient[1]. The initial focus of the effort is processing C100 cavities by injecting RF power into the HOM coupler ports. The goal will be to improve the operational gradients and the energy margin of the CEBAF linacs by processing cryomodules in situ. Results from processing cryomodule in the cryomodule test bunker as well as vertical test results will be present-ed. This work will describe the systems and methods used at JLAB for processing cavities using an argon oxygen gas mixture. Before and after plasma processing results will also be presented.

Powers, T.↗
DOE OSTI2020

AGGREGATE: dAta-driven modelinG preservinG contRollable dEr for outaGe mAnagemenT and rEsiliency (Report for Task 10: Controllability and Observability Analysis (Deliverable D7))

It is common to have less than full observability for distribution systems, as the number of available measurements are not sufficient. Considering increasing penetration of distributed energy resources (DERs), it is imperative to understand and control distribution systems better. Developed for the transmission system, the original numerical observability analysis methods were based on the canonical DC Power Flow (DC-PF) model. However, the DC-PF model is ill-suited for the distribution system in which line resistance to reactance (R/X) ratios can be near unity. In this report, we apply the non-iterative Observability Test (OT) and Observable Island Identification Procedure (OIIP) in to the gain matrix from the distribution system state estimator. Because sensors are few in distribution systems, pseudo-measurements based on historical load profiles and zero-injection virtual measurements are often employed to ensure observability. However, both the observability and the accuracy of the state estimates are uncertain when historical data is limited/unavailable.

42 ENGINEERING↗
DOE OSTI2022

Kinematic Evidence for an Embedded Planet in the IM Lupi Disk

Abstract We test the hypothesis that an embedded giant planet in the IM Lupi protostellar disk can produce velocity kinks seen in CO line observations as well as the spiral arms seen in scattered light and continuum emission. We inject planets into 3D hydrodynamics simulations of IM Lupi, generating synthetic observations using Monte Carlo radiative transfer. We find that an embedded planet of 2–3 M Jup can reproduce non-Keplerian velocity perturbations, or “kinks”, in the 12 CO J = 2–1 channel maps. Such a planet can also explain the spiral arms seen in 1.25 mm dust continuum emission and 1.6 μ m scattered-light images. We show that the wake of the planet can be traced in the observed peak velocity map, which appears to closely follow the morphology expected from our simulations and from analytic models of planet–disk interaction.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Effects of stratification and charge cooling on combustion in a gasoline direct-injection compression ignition (GDCI) engine

With the development of low temperature engine combustion strategies, performance of gasoline-type fuels under compression ignition conditions has attracted extensive research interest. Meanwhile, for the sake of co-optimization of engines and fuels for future ground transportation, identification and evaluation of general fuel properties should be a core research priority instead of endless testing of specific fuels. In this study, the roles of fuel octane sensitivity in characterizing the ignition performance of gasoline surrogates have been systematically investigated under typical gasoline direct ignition compression ignition (GDCI) engine conditions using 3D combustion CFD simulation, especially considering the subsequent in-cylinder charge stratification and charge cooling. Two different operating conditions, high boost pressure low boost temperature (beyond-RON) case and low boost pressure high boost temperature (beyond-MON) case, were considered. By comparing with our previous zero-dimensional chemical kinetic study of gasoline surrogates in advanced compression ignition (ACI) engines, the effects of stratification and charge cooling on the combustion processes are investigated. It is found that different fuel octane sensitivities lead to slight difference in equivalence ratio stratification and charge cooling due to differences in volatility. However, fuel reactivity is still the more dominant factor than the stratification and charge cooling effects in determining combustion phasing. The present results help to justify the P-T domain framework for engine autoignition analysis of overlapping pressure-temperature trajectory with ignition delay iso-contour. Here, the results also provide useful guidance to the understanding of GCI combustion process, and to the evaluation of controlling fuel properties and the selection of alternative fuels in GCI engines.

33 ADVANCED PROPULSION SYSTEMS↗