SEARCH · Engineering Papers
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.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
This paper derives a state-space model for model predictive control of a high temperature gas micro-reactor based on the Holos-Quad Design.
The solar cycle 25 progression is ramping up, prompting satellite operators to provide estimates of propellent usage over the next several years. Drag due to atmospheric heating from solar activity is the main driver to satellite lifetime decay, especially for those in low-Earth orbit destinations. In this poster, several model predictions of the sunspot number are compared and discussed with comments on applicability to engineering programs.
Thermal energy storage (TES) can enable more building-sited renewable electricity generation and lower utility bill costs for buildings owners and occupants, especially when there are high demand and variable time-of-use (TOU) charges. A model predictive control (MPC) strategy can offer additional savings over a schedule-based control with added complexity and reliance on forecasts. Here, this study examines savings for medium office buildings with chiller plants in three locations with building-installed solar photovoltaics (PV) to understand the impact of MPC. Control setpoints are fixed by a schedule-based control or optimized by nonlinear MPC. These control setpoints are actuated within EnergyPlus building models to simulate the utility cost of the chiller plant. NLP solutions can be unstable or unrealistic, but our results show that by regularizing the NLP, the solutions can be reasonably followed by the building model. MPC models make simplifications that lead to errors once the controller is participating in and changing the operation of the building. These errors average 9 % across the cases, showing that the most important parts of the system are represented. The no-thermal load costs are computed to show that the optimization can in some cases achieve both the minimum TOU and minimum monthly demand costs by demand management while reducing TOU energy costs by energy arbitrage. The MPC saves 35–66 % in the annual chiller plant operating costs, which is an additional savings above the schedule by 1–33 %. PV and TES are complementary and mostly independent, but a load with PV often results in better performance for the schedule. Our case study and sensitivity analysis show the importance of modeling and optimization for complex rates, but also the circumstances wherein a simpler strategy achieves the same performance with less potential for error.
Bio-mathematical fatigue models that predict levels of alertness and performance are one potential tool for use within integrated fatigue risk management approaches. A number of models have been developed that provide predictions based on acute and chronic sleep loss, circadian desynchronization, and sleep inertia. Some are publicly available and gaining traction in settings such as commercial aviation as a means of evaluating flight crew schedules for potential fatigue-related risks. Yet, most models have not been rigorously evaluated and independently validated for the operations to which they are being applied and many users are not fully aware of the limitations in which model results should be interpreted and applied.
As electrified aircraft propulsion (EAP) systems continue to mature, more sophisticated hardware and software are being developed to balance operations among electric machines and gas-turbine engines. In hybrid-electric propulsion systems, the increased complexity resulting from integrating turbine-engine shafts with electric machines necessitates control methodologies to account for various physical domains. Ideal controllers for hybrid-electric engines manage systems, subsystems, and their interactions in a coordinated fashion, able to account for safety and performance goals while being computationally efficient. In a previous work, linear model predictive control (MPC) schemes were implemented in centralized and distributed frameworks on a nonlinear turbofan engine model as a proof of concept. However, these schemes were not evaluated for computational complexity, prompting further study. The research presented here develops hierarchical MPC schemes to reduce the computational burden of the previous MPC schemes. A two-tier framework is implemented, where a slower sampling MPC controls electric machines and determines fan-speed tracking goals for a faster sampling controller, which is either a MPC or a proportional-integral (PI) controller. The proposed designs are compared to the centralized MPC investigated previously, and performance is measured via fan speed tracking error, energy storage state-of-charge, and computation time. Results reveal that the hierarchical MPC scheme employing a lower-level PI controller improves computation time while maintaining comparable tracking and state-of-charge regulation to the centralized scheme.
As electrified aircraft propulsion (EAP) systems continue to mature, more sophisticated hardware and software are being developed to balance operations among electric machines and gas-turbine engines. In hybrid-electric propulsion systems, the increased complexity resulting from integrating turbine-engine shafts with electric machines necessitates control methodologies to account for various physical domains. Ideal controllers for hybrid-electric engines manage systems, subsystems, and their interactions in a coordinated fashion, able to account for safety and performance goals while being computationally efficient. In a previous work, linear model predictive control (MPC) schemes were implemented in centralized and distributed frameworks on a nonlinear turbofan engine model as a proof of concept. However, these schemes were not evaluated for computational complexity, prompting further study. The research presented here develops hierarchical MPC schemes to reduce the computational burden of the previous MPC schemes. A two-tier framework is implemented, where a slower sampling MPC controls electric machines and determines fan-speed tracking goals for a faster sampling controller, which is either a MPC or a proportional-integral (PI) controller. The proposed designs are compared to the centralized MPC investigated previously, and performance is measured via fan speed tracking error, energy storage state-of-charge, and computation time. Results reveal that the hierarchical MPC scheme employing a lower-level PI controller improves computation time while maintaining comparable tracking and state-of-charge regulation to the centralized scheme.
The goal of this project is to develop integrated, state-of-the-art, computational modeling tools based on an integrated computational materials engineering (ICME) methodology that are critically needed to enable structural carbon fiber (CF) applications in automobiles. These tools are designed to predict the manufacturing and structural performance of CF composites, including stochastic effects. During the first phase of the project, the manufacturing and structural performance tools, including a stochastic driver, were developed, calibrated, and validated against coupon and component level test results. For this project, from the manufacturing side, the development efforts were focused on high-pressure resin transfer molding (HP-RTM), a potentially game-changing manufacturing technology that is capable of reaching the 3-5-minute cycle time that is necessary for volume manufacturing of composites. On the structural performance side, the crashworthiness of CF structures was studied. Accordingly, computational tools were developed and validated. The resulting differences between the numerical predictions and the experimental results in the first phase of the project were required to be less than 15%. During the second phase of the project, the manufacturing and performance tools were integrated by mapping the manufacturing outcomes (e.g., fiber angles, residual stresses, degree of cure, and defects) into the structural models. Also, using the tools developed in this project, an automotive assembly currently manufactured in steel (2016 GM Malibu) was redesigned to be manufactured using advanced CF composites with the objective of comparing the performance of the CF assembly with the developed ICME model predictions. The weight, performance and cost of the CF assembly were compared with the baseline steel assembly as well. The CF underbody design was shown to be 30% lighter than the corresponding steel design. The CF underbody assembly withstood the side pole impact with less than half the intrusion for the steel assembly. Excellent correlations within 10% for both peak impact load and intrusion were observed between the numerical predictions and experimental results. Based on the cost models developed in the project, the cost increase per Kg saved was determined to be $22. The project team has prepared a total of 28 publications in various journals and conferences and broadly communicated the project results for the benefit of the composite industry. The project team has also prepared a total of 10 patent applications that were submitted to the US Patent and Trademark office.
The Air Force has developed PCBoom3, a general-purpose, single-event sonic boom prediction model. The model operates on an IBM PC or compatible, under DOS or Windows. It is accessed via an integrated environment which controls building of input cases, running boom calculations, displaying contours and signatures, and managing all associated data. The primary boom calculation is via a variation of FOBOOM, the focus-boom extension of Thomas's program. Aircraft input is either via a user-provided F-function, or simple N-wave F-functions tabulated for about 20 current aircraft. A fast boom calculation, based on Plotkin's SBORT algorithms, is included for simple N-wave F-functions in a windless atmosphere and flight altitudes up to 60,000 feet. After a run is complete, the user can access an index identifying significant events (focal zones, beginning of footprint, etc.), then plot boom amplitude contours and signatures or spectra at any point in the footprint. The primary uses of this program are expected to be operational planning and boom incident investigation. However, because of the commonality between FOBOOM and the MDBOOM program currently being used for low boom configuration design, this program is of interest to the HSCT community, especially as supersonic route planning activity increases. The Air Force recently conducted a flight test program to evaluate the focal zone capabilities of PCBoom3. Initial results of that program validate the prediction of focal zone geometry, amplitudes, and waveforms.
With the increasing application of power converters in distributed energy systems, power electronics converters face an increasing number of cyber-attacks. To mitigate the cyber-attack impact on voltage source converters (VSCs) and microgrids, a robust model predictive control (RMPC) is proposed for virtual synchronous generators (VSG) in an islanded microgrid. This RMPC is designed to compensate for the frequency deviations, thus maintaining frequency stability of the whole islanded microgrid against cyber threats. Finally, to verify the feasibility of the proposed method, comparisons between the proposed method and the conventional VSC controller are provided in different attack scenarios.
NRX/EST nuclear rocket test system transfer function measurements by control drum perturbation, and comparison with analysis model predictions
This paper describes a model-predictive automatic recovery system for aircraft on the verge of a loss-of-control situation. The system determines when it must intervene to prevent an imminent accident, resulting from a poor approach. It estimates the altitude loss that would result from a go-around maneuver at the current flight condition. If the loss is projected to violate a minimum altitude threshold, the maneuver is automatically triggered. The system deactivates to allow landing once several criteria are met. Piloted flight simulator evaluation showed the system to provide effective envelope protection during extremely unsafe landing attempts. The results demonstrate how flight and propulsion control can be integrated to recover control of the vehicle automatically and prevent a potential catastrophe.
This paper describes a model-predictive automatic recovery system for aircraft on the verge of a loss-of-control situation. The system determines when it must intervene to prevent an imminent accident, resulting from a poor approach. It estimates the altitude loss that would result from a go-around maneuver at the current flight condition. If the loss is projected to violate a minimum altitude threshold, the maneuver is automatically triggered. The system deactivates to allow landing once several criteria are met. Piloted flight simulator evaluation showed the system to provide effective envelope protection during extremely unsafe landing attempts. The results demonstrate how flight and propulsion control can be integrated to recover control of the vehicle automatically and prevent a potential catastrophe.
Osteoradionecrosis (ORN) of the mandible represents a severe, debilitating complication of radiation therapy (RT) for head and neck cancer (HNC). At present, no normal tissue complication probability (NTCP) models for risk of ORN exist. The aim of this study was to develop a multivariable clinical/dose-based NTCP model for the prediction of ORN any grade (ORN{sub I-IV}) and grade IV (ORN{sub IV}) after RT (±chemotherapy) in patients with HNC.
Model supplements biological surveys of spacecraft by simulating microbial burden accumulation process during periods when surveys are not taken. Important application of model is to predict microbial loading on spacecraft landing capsule immediately prior to terminal heat sterilization.
Partially Stabilized Zirconia (PSZ) may become widely used for Thermal Barrier Coatings (TBC). Failure of these coatings can occur due to thermal fatigue in oxidizing atmospheres. The failure is due to the strains that develop due to thermal gradients, differences in thermal expansion coefficients, and oxidation of the bond coating. The role of microstructure and the cubic, tetragonal, and monoclinic phase distribution in the strain development and subsequent failure will be discussed. An X-ray diffraction technique for accurate determination of the fraction of each phase in PSZ will be applied to understanding the phase transformations and strain development. These results will be discussed in terms of developing a model for life prediction in PSZ coatings during thermal cycling.
This report provides progress to test the predictions of substorm models using ISTP observations. During the first year, two investigations were initiated in collaboration with a number of ISTP researchers. Both investigations use a combination of simultaneous measurements from high-, low-, and ground-altitude instruments to: (1) explore the role of MHD resonances in the onset and evolution of substorms, and (2) establish the timing of events in the magnetosphere and ionosphere during the substorm evolution beginning with the growth phase and ending with the recovery phase.
We investigate the time-variable gravity changes in Europe retrieved from the initial GRACE monthly solutions spanning a 18 month duration from April 2002 to October 2003. Gravity anomaly maps are retrieved in Central Europe from the monthly satellite solutions we compare the fields according to various truncation levels (typically between degree 10 and 20) of the initial fields (expressed in spherical harmonics to degree 120). For these different degrees, an empirical orthogonal function (EOF) decomposition of the time-variable gravity field leads us to its main spatial and temporal characteristics. We show that the dominant signal is found to be annual with an amplitude and a phase both in agreement with predictions in Europe modeled using snow and soil-moisture variations from recent hydrology models. We compare these GRACE gravity field changes to surface gravity observations from 6 superconducting gravimeters of the GGP (Global Geodynamics Project) European sub-network, with a special attention to loading corrections. Initial results suggest that all 3 data sets (GRACE, hydrology and GGP) are responding to annual changes in near-surface water in Europe of a few microGal (at length scales of approx.1000 km) that show a high value in winter and a summer minimum. We also point out that the GRACE gravity field evolution seems to indicate that there is a trend in gravity between summer 2002 and summer 2003 which can be related to the 2003 heatwave in Europe and its hydrological consequences (drought). Despite the limited time span of our analysis and the uncertainties in retrieving a regional solution from the network of gravimeters, the calibration and validation aspects of the GRACE data processing based on the annual hydrology cycle in Europe are in progress.
Four-switch buck-boost converter supports both voltage step-up and step-down functionalities, but it suffers from mode transfer challenge that would need reliable mode detection when designed to operate in multi different modes. In this paper, a novel control method based on model predictive current control is proposed for such converter with inherent smooth mode transfer capability without extra design on mode detection and transfer scheme. Modulator and mode detection are replaced by an optimization process through cost function. This largely simplifies the design and makes it easily implemented. Therefore, seamless transfer between buck and boost modes is achieved with many other system level benefits. Simulation and experimental results are provided to verify the effectiveness of proposed method for the four-switch buck-boost converter.