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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 37 records · Page 2

Molecular Level Understanding of Polyethylene Terephthalate (PET) Depolymerization in Base/Alcohol Hybrid Systems

Polyethylene terephthalate (PET) depolymerization in base/alcohol hybrid systems represents a promising low-energy approach for chemically recycling PET waste into valuable monomers. This study investigates the mechanistic pathways of PET depolymerization in NaOH/alcohol solutions, emphasizing the competing roles of hydroxide and alkoxide species. Utilizing a combination of experimental techniques, density functional theory (DFT) calculations, and molecular dynamics (MD) simulations, we explore how factors such as base concentration, alcohol chain length, and pKa values of alcohols influence PET depolymerization efficiency and pathways. Our findings indicate that alkoxide ions (RO⁻) exhibit notably higher reactivity than hydroxide ions (HO⁻), favoring an alcoholysis pathway in the base/alcohol hybrid system. Experimental results across a series of C1 to C5 alcohols show that longer-chain alcohols, particularly 1-butanol, achieve higher PET conversion, although this does not align solely with simple nucleophilicity trends of alkoxides. While DFT calculations reveal comparable activation energies for various alkoxides in PET depolymerization, MD simulations underscore the significant role of alcohol chain length, with longer-chain alcohols forming more stable or frequent interactions with PET. Additionally, the alkoxide concentration, influenced by the alcohol’s pK a , directly impacts PET conversion. These suggest that PET depolymerization is governed by a balance between alkoxide concentration and alkoxide-PET interactions, rather than activation energies or nucleophilicity alone. From a practical perspective, incorporating long-chain alcohols as cosolvents may enhance process efficiency but increases raw material costs by approximately 30%. However, long-chain alcohols present a safer and more sustainable alternative to hazardous cosolvents such as dichloromethane. This work offers a molecular-level understanding of PET depolymerization in base/alcohol systems and provides insights into optimizing these systems for more efficient and sustainable PET recycling processes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Combining Particle Filters and Consistency-Based Approaches for Monitoring and Diagnosis of Stochastic Hybrid Systems

Fault detection and isolation are critical tasks to ensure correct operation of systems. When we consider stochastic hybrid systems, diagnosis algorithms need to track both the discrete mode and the continuous state of the system in the presence of noise. Deterministic techniques like Livingstone cannot deal with the stochasticity in the system and models. Conversely Bayesian belief update techniques such as particle filters may require many computational resources to get a good approximation of the true belief state. In this paper we propose a fault detection and isolation architecture for stochastic hybrid systems that combines look-ahead Rao-Blackwellized Particle Filters (RBPF) with the Livingstone 3 (L3) diagnosis engine. In this approach RBPF is used to track the nominal behavior, a novel n-step prediction scheme is used for fault detection and L3 is used to generate a set of candidates that are consistent with the discrepant observations which then continue to be tracked by the RBPF scheme.

Narasimhan, Sriram↗

Techno-Economic Analysis of Solid Oxide Fuel Cell-Gas Turbine Hybrid Systems for Stationary Power Applications Using Renewable Hydrogen

Solid oxide fuel cell (SOFC)–gas turbine (GT) hybrid systems can produce power at high electrical efficiencies while emitting virtually zero criteria pollutants (e.g., ozone, carbon monoxide, oxides of nitrogen and sulfur, and particulate matters). This study presents new insights into renewable hydrogen (RH 2 )-powered SOFC–GT hybrid systems with respect to their system configuration and techno-economic analysis motivated by the need for clean on-demand power. First, three system configurations are thermodynamically assessed: (I) a reference case with no SOFC off-gas recirculation, (II) a case with cathode off-gas recirculation, and (III) a case with anode off-gas recirculation. While these configurations have been studied in isolation, here we provide a detailed performance comparison. Moreover, a techno-economic analysis is conducted to study the economic competitiveness of RH 2 -fueled hybrid systems and the economies of scale by offering a comparison to natural gas (NG)-fueled systems. Results show that the case with anode off-gas recirculation, with 68.50%-lower heating value (LHV) at a 10 MW scale, has the highest efficiency among the studied scenarios. When moving from 10 MW to 50 MW, the efficiency increases to 70.22%-LHV. These high efficiency values make SOFC–GT hybrid systems highly attractive in the context of a circular economy as they outcompete most other power generation technologies. The cost-of-electricity (COE) is reduced by about 10% when moving from 10 MW to 50 MW, from USD 1976/kW to USD 1668/kW, respectively. Renewable H 2 is expected to be economically competitive with NG by 2030, when the U.S. Department of Energy’s target of USD 1/kg RH 2 is reached.

25 ENERGY STORAGE↗

A Structural Model Decomposition Framework for Hybrid Systems Diagnosis

Nowadays, a large number of practical systems in aerospace and industrial environments are best represented as hybrid systems that consist of discrete modes of behavior, each defined by a set of continuous dynamics. These hybrid dynamics make the on-line fault diagnosis task very challenging. In this work, we present a new modeling and diagnosis framework for hybrid systems. Models are composed from sets of user-defined components using a compositional modeling approach. Submodels for residual generation are then generated for a given mode, and reconfigured efficiently when the mode changes. Efficient reconfiguration is established by exploiting causality information within the hybrid system models. The submodels can then be used for fault diagnosis based on residual generation and analysis. We demonstrate the efficient causality reassignment, submodel reconfiguration, and residual generation for fault diagnosis using an electrical circuit case study.

structural model decomposition↗

Acceptance Testing of a Satellite SCADA Photovoltaic-Diesel Hybrid System

Satellite Supervisory Control and Data Acquisition (SCADA) of a Photovoltaic (PV)/diesel hybrid system was tested using NASA's Advanced Communication Technology Satellite (ACTS) and Ultra Small Aperture Terminal (USAT) ground stations. The setup consisted of a custom-designed PV/diesel hybrid system, located at the Florida Solar Energy Center (FSEC), which was controlled and monitored at a "remote" hub via Ka-band satellite link connecting two 1/4 Watt USATs in a SCADA arrangement. The robustness of the communications link was tested for remote monitoring of the health and performance of a PV/diesel hybrid system, and for investigating load control and battery charging strategies to maximize battery capacity and lifetime, and minimize loss of critical load probability. Baseline hardware performance test results demonstrated that continuous two-second data transfers can be accomplished under clear sky conditions with an error rate of less than 1%. The delay introduced by the satellite (1/4 sec) was transparent to synchronization of satellite modem as well as to the PV/diesel-hybrid computer. End-to-end communications link recovery times were less than 36 seconds for loss of power and less than one second for loss of link. The system recovered by resuming operation without any manual intervention, which is important since the 4 dB margin is not sufficient to prevent loss of the satellite link during moderate to heavy rain. Hybrid operations during loss of communications link continued seamlessly but real-time monitoring was interrupted. For this sub-tropical region, the estimated amount of time that the signal fade will exceed the 4 dB margin is about 10%. These results suggest that data rates of 4800 bps and a link margin of 4 dB with a 1/4 Watt transmitter are sufficient for end-to-end operation in this SCADA application.

Kalu, A.↗

Technical, economic, and load-following capabilities assessment of grid-connected geothermal and geothermal-solar hybrid systems

The technical and economic performance as well as the load-following capabilities of grid-connected geothermal hybrid systems were assessed in this work. The analyzed geothermal hybrid configuration is composed of a binary geothermal plant integrated with a concentrating solar-thermal system and underground thermal energy storage (UTES) through a primary heat exchanger. Physics-based models for the hybrid system for plant generation capacities of 1, 25, and 50 MW were developed from validated models for each subsystem. Also, an economic model was developed that accounts for different hybrid system capabilities, solar field sizes, and thermal storage duration. The advantage of the geothermal hybrid system was assessed by comparing the performance with the baseline benchmark geothermal plant with a similar configuration and generation capacity. It was found that hybridizing geothermal plants with concentrating solar and thermal energy storage not only improves the thermal efficiency by up to 8 percentage points when additional heat from the solar-UTES loop rises the evaporator temperatures from 70 to 125 °C, but also enhances the load-following capability for the geothermal plant, which can meet a typical residential load profile with a power rate of change 0.25 kW/s with an absolute error under 13 kW for a 1 MW plant. Other benefits of hybridization include resource preservation and a potential LCOE reduction of up to 56% for a 50 MW geothermal hybrid plant having a 50% solar share, a 1.4 solar multiple, and 24-h storage capacity. The results presented in this work demonstrate that hybridizing geothermal systems transforms them into a flexible and cost-effective solution for addressing the dynamic requirements of modern electric grids.

15 GEOTHERMAL ENERGY↗

Diagnosing Hybrid Systems: a Bayesian Model Selection Approach

In this paper we examine the problem of monitoring and diagnosing noisy complex dynamical systems that are modeled as hybrid systems-models of continuous behavior, interleaved by discrete transitions. In particular, we examine continuous systems with embedded supervisory controllers that experience abrupt, partial or full failure of component devices. Building on our previous work in this area (MBCG99;MBCG00), our specific focus in this paper ins on the mathematical formulation of the hybrid monitoring and diagnosis task as a Bayesian model tracking algorithm. The nonlinear dynamics of many hybrid systems present challenges to probabilistic tracking. Further, probabilistic tracking of a system for the purposes of diagnosis is problematic because the models of the system corresponding to failure modes are numerous and generally very unlikely. To focus tracking on these unlikely models and to reduce the number of potential models under consideration, we exploit logic-based techniques for qualitative model-based diagnosis to conjecture a limited initial set of consistent candidate models. In this paper we discuss alternative tracking techniques that are relevant to different classes of hybrid systems, focusing specifically on a method for tracking multiple models of nonlinear behavior simultaneously using factored sampling and conditional density propagation. To illustrate and motivate the approach described in this paper we examine the problem of monitoring and diganosing NASA's Sprint AERCam, a small spherical robotic camera unit with 12 thrusters that enable both linear and rotational motion.

McIlraith, Sheila A.↗

Qualitative Fault Isolation of Hybrid Systems: A Structural Model Decomposition-Based Approach

Quick and robust fault diagnosis is critical to ensuring safe operation of complex engineering systems. A large number of techniques are available to provide fault diagnosis in systems with continuous dynamics. However, many systems in aerospace and industrial environments are best represented as hybrid systems that consist of discrete behavioral modes, each with its own continuous dynamics. These hybrid dynamics make the on-line fault diagnosis task computationally more complex due to the large number of possible system modes and the existence of autonomous mode transitions. This paper presents a qualitative fault isolation framework for hybrid systems based on structural model decomposition. The fault isolation is performed by analyzing the qualitative information of the residual deviations. However, in hybrid systems this process becomes complex due to possible existence of observation delays, which can cause observed deviations to be inconsistent with the expected deviations for the current mode in the system. The great advantage of structural model decomposition is that (i) it allows to design residuals that respond to only a subset of the faults, and (ii) every time a mode change occurs, only a subset of the residuals will need to be reconfigured, thus reducing the complexity of the reasoning process for isolation purposes. To demonstrate and test the validity of our approach, we use an electric circuit simulation as the case study.

Hybrid Systems Diagnosis↗

Majorana modes with side features in magnet-superconductor hybrid systems

Magnet-superconductor hybrid (MSH) systems represent promising platforms to host Majorana zero modes (MZMs), the elemental building blocks for fault-tolerant quantum computers. Theoretical description of such MSH structures is mostly based on simplified models, not accounting for the complexity of real materials. Here, based on density functional theory, we derive a superconducting 80-band model to study an MSH system consisting of a magnetic manganese chain on the s wave superconductor niobium. For a wide range of values of the superconducting order parameter, the system is a topological superconductor, with MZMs exhibiting non-universal spatial patterns and a drastic accumulation of spectral weight on both sides along the magnetic chain. These side feature states can be explained by an effective model which is guided by the ab initio results. Performing scanning tunneling spectroscopy experiments on the same system, we observe a spatial structure in the low-energy local density of states that is consistent with the theoretical findings. Our results open a first-principle approach to the discovery of topological superconductors.

36 MATERIALS SCIENCE↗

Mean-field limit of a hybrid system for multi-lane multi-class traffic

This article aims to study coupled mean-field equation and ODEs with discrete events motivated by vehicular traffic flow. Precisely, multi-lane traffic flow in presence of human-driven and autonomous vehicles is considered, with autonomous vehicles possibly influenced by external policymakers. First, a finite-dimensional hybrid system is developed based on the continuous Bando-Follow-the-Leader dynamics coupled with discrete events due to lane-change maneuvers. Then the mean-field limit of the finite-dimensional hybrid system is rigorously derived for the dynamics of the human-driven vehicles. The microscopic lane-change maneuvers of the human-driven vehicles generate a source term for the mean-field PDE. This leads to an infinite-dimensional hybrid system described by coupled Vlasov-type PDE, ODEs, and discrete events.

97 MATHEMATICS AND COMPUTING↗

Synthesis from Design Requirements of a Hybrid System for Transport Aircraft Longitudinal Control

Volume I of this report presents a new method for synthesizing hybrid systems directly from design requirements, and applies the method to design of a hybrid system for longitudinal control of transport aircraft. The resulting system satisfies general requirement for safety and effectiveness specified a priori, enabling formal validation to be achieved. Volume II contains seven appendices intended to make the report accessible to readers with backgrounds in human factors, fli ght dynamics and control. and formal logic. Major design goals are (1) system desi g n integrity based on proof of correctness at the design level, (2), significant simplification and cost reduction in system development and certification, and (3) improved operational efficiency, with significant alleviation of human-factors problems encountered by pilots in current transport aircraft. This report provides for the first time a firm technical basis for criteria governing design and certification of avionic systems for transport aircraft. It should be of primary interest to designers of next-generation avionic systems.

Hynes, Charles S.↗

Synthesis from Design Requirements of a Hybrid System for Transport Aircraft Longitudinal Control

Volume I of this report presents a new method for synthesizing hybrid systems directly from desi gn requirements, and applies the method to design of a hybrid system for longitudinal control of transport aircraft. The resulting system satisfies general requirement for safety and effectiveness specified a priori, enabling formal validation to be achieved. Volume II contains seven appendices intended to make the report accessible to readers with backgrounds in human factors, flight dynamics and control, and formal logic. Major design goals are (1) system design integrity based on proof of correctness at the design level, (2) significant simplification and cost reduction in system development and certification, and (3) improved operational efficiency, with significant alleviation of human-factors problems encountered by pilots in current transport aircraft. This report provides for the first time a firm technical basis for criteria governing design and certification of avionic systems for transport aircraft. It should be of primary interest to designers of next-generation avionic systems.

Hynes, Charles S.↗

Hybrid Systems Diagnosis

This paper reports on an on-going Project to investigate techniques to diagnose complex dynamical systems that are modeled as hybrid systems. In particular, we examine continuous systems with embedded supervisory controllers that experience abrupt, partial or full failure of component devices. We cast the diagnosis problem as a model selection problem. To reduce the space of potential models under consideration, we exploit techniques from qualitative reasoning to conjecture an initial set of qualitative candidate diagnoses, which induce a smaller set of models. We refine these diagnoses using parameter estimation and model fitting techniques. As a motivating case study, we have examined the problem of diagnosing NASA's Sprint AERCam, a small spherical robotic camera unit with 12 thrusters that enable both linear and rotational motion.

McIlraith, Sheila↗

Cyber-Physical Simulation of the Cold Startup of Solid Oxide Fuel Cell – Gas Turbine (SOFC-GT) Hybrid Systems

This work introduces experimental studies for the cold startup process (CPS) of the SOFC-GT hybrid system using the cyber-physical simulation approach. The physical gas turbine is coupled with a cyber-physical SOFC stack, which is represented using the integration of a real time dynamic SOFC model with physical components (e.g., pressure chamber, natural gas burner, etc.). Different ramp rates of the turbine speed were tested out during the startup processes. Bypass valves were also used to manipulate the airflow during SOFC-GT hybrid system start-up process. Different ramp rates enable the rapid start-up of the turbine to avoid surge and stall, meanwhile enable acceptable warm rate of the fuel cell stack without damaging the cell material. CPS can enable dynamic characterizations of highly integrated systems at lower cost.

Zhou, Nana↗