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DOE OSTI2026

A tissue‐resolved, network‐based transcriptomic framework for abiotic stress responses in sorghum

Developing climate‐resilient crops requires a detailed understanding of stress‐induced gene expression dynamics, as maladaptive responses can compromise their productivity and survival. Sorghum, a globally important cereal with exceptional tolerance to multiple abiotic stresses, provides a powerful system for investigating these dynamics. However, how stress type, tissue specificity, and temporal progression jointly shape transcriptomic responses in crops remains poorly understood. Here, we present a comparative, time‐resolved transcriptomic atlas of sorghum responses to drought, heat, and salinity stress across shoot and root tissues. Integrative analyses revealed that tissue specificity is the dominant determinant of abiotic stress‐induced gene reprogramming across all three stresses. Building on these global comparisons, we focused on heat stress, as it elicited the most coherent and pronounced transcriptional and regulatory responses, enabling deeper network‐level interrogation. Co‐expression network analysis identified tissue‐specific modules enriched for phytohormone‐responsive genes, while gene regulatory network (GRN) mapping and cistrome analyses uncovered transcription factors (TFs) controlling key hub genes within these modules. Together, this study provides a foundational transcriptomic and network‐based resource for dissecting the regulatory architecture of abiotic stress responses in sorghum and offers prioritized candidates for future functional validation and engineering of climate‐resilient crops.

abiotic stress↗

NASA NTRSDate not supplied

Revisiting the Soyuz-1 Parachute Failure in the Context of Safety in the Modern Era

The Soyuz‑1 accident remains one of the most consequential parachute related failures in human spaceflight history and provides enduring lessons for modern Entry, Descent, and Landing (EDL) system design. Occurring during the height of the Cold War and the Space Race, the mission unfolded under extraordinary political and schedule pressure as the Soviet Union sought to maintain its early leadership in space achievements following the death of chief designer Sergei Korolev. Despite unresolved propulsion, electrical, and parachute system deficiencies, Soyuz‑1 proceeded to launch and immediately encountered critical inflight anomalies, including a failed solar panel deployment, attitude control issues, and communication dropouts. Upon reentry, a malfunction in the parachute system, driven by a primary main canopy that failed to deploy, and subsequent entanglement of the reserve main canopy with the primary drogue parachute, resulted in insufficient deceleration and the fatal crash of cosmonaut Vladimir Komarov. Subsequent investigations revealed deep rooted cultural and organizational issues within the Soviet space program, including inadequate testing, suppression of dissent, undocumented last minute design changes, and the absence of integrated parachute system verification. More than 200 design flaws were identified after the accident, and firsthand accounts, including those from Yuri Gagarin, highlighted widespread concern prior to launch. Over time, the Soviet program implemented substantial reforms: systematic design corrections, rigorous process documentation, and an extensive series of drop tests that ultimately transformed the Soyuz system into one of the world’s most reliable human-rated return vehicles. This paper examines the technical architecture of the Soyuz‑1 parachute system, reconstructs the likely deployment sequence and failure mechanism, and analyzes the cultural contributors that shaped the accident. The study draws parallels to modern spacecraft parachute development, emphasizing the critical importance of integrated system testing, transparent engineering culture, and continuous hardware surveillance. These lessons remain directly relevant to today’s NASA and Commercial Crew Programs (CCP), where the Government continues to refine its understanding of aggregate risk and strengthen overall astronaut safety in the face of increasingly complex parachute systems.

Aaron L Morris↗

NASA NTRS2022

Remote Diagnosis and Operational Response to an In-Flight Failure of the Drill Feed Mechanism Onboard the Mars Science Laboratory Rover

On November 30th, 2016 (Sol 1536 of the mission), the Mars Science Laboratory (MSL) flight operations team commanded the Curiosity rover to drill into a Martian rock to acquire the mission’s 16th rock powder sample. The drilling operation was halted when the drill feed mechanism unexpectedly stalled shortly after disengaging its magnetically-actuated friction brake at the start of a long move to extend the drill bit into contact with the target rock. The drilling campaign was put on hold and later abandoned as diagnostic experimentation revealed a tendency for the actuator to transition in and out of a high-drag state in which the mechanism could not actuate. In the subsequent months, the team conducted a variety of in-flight and ground-based investigations to determine root cause and identify mitigation strategies for continued operation. Mechanism reliability continued to degrade and by June 2017, it became clear that the mechanism could not be relied upon to support drilling operations. The team succeeded in fully extending the feed, enabling the development of new sampling techniques that would not rely on the feed mechanism. The first feed-extended drilling sample was successfully collected on Sol 2057, 521 sols after the initial feed stall. This paper discusses the anomaly investigation process, failure analysis, and feed mechanism operation mitigation strategies. It concludes with key lessons learned about mechanism design, mission architecture, and operational best practices.

Lin, Megan Richardson↗

NASA NTRS2001

Integrated Modeling for the Next Generation Space Telescope "Yardstick" Concept

The so-called NASA "Yardstick" design concept for the Next Generation Space Telescope presents unique challenges for systems-level analysis. Simulations that integrate controls, optics, thermal, and structural models are required to evaluate baseline performance, study design sensitivities, and perform design optimization. An integrated modeling approach was chosen using a combination of commercial off-the-shelf and "in-house" developed codes. The resulting capability provides a foundation for linear and non-linear analysis, using both the time and frequency-domain methods. It readily allows various combinations of design parameters and environmental loads to be evaluated directly in terms of key science-related metrics, in this case the scalar RMS (root mean square) line-of-sight and RMS wavefront errors. This presentation first addresses the development of the component, or discipline, models for the Yardstick design. It will then proceed to present the integration of the component models, using linear-systems approaches, in order to support two of the most critical baseline performance analyses: jitter and thermal-elastic stability of the optical telescope assembly (OTA). The results of the jitter analysis indicate that disturbances from the reaction wheels coupled with the lightly-damped and highly-flexible structure present significant challenges to the baseline line-of-sight control architecture. Vibration isolation will be required to meet jitter error requirements. The results of the thermal-elastic analysis indicate that the mirror segment displacements due to ground-to-orbit cool-down of the telescope are within the expected capture range of the segment rigid-body control actuators. This means we will be able to align and phase the primary mirror. However, the results for the analysis of the thermal transient response following an attitude maneuver (slew) show that this telescope design is not sufficiently stable, passively, to meet the wavefront error requirements. Structural re-design is one possibility; alternatively, active thermal control of the OTA may be considered. The Yardstick integrated models were successfully used to demonstrate the feasibility of two thermal control strategies.

Mosier, Gary E.↗

NASA NTRS2021

A Spectrum Sensor for CubeSat Radios

Cube satellite (CubeSat) launches have increased exponentially over the last 20 years. This class of miniature spacecraft is well-suited for a set of nonconventional satellite architectures collectively known as formation flying. With the exponential pace of launches expected to continue, the prospect of spectrum management for these complex formations arises. In previous work, investigators focus on terrestrial applications of spectrum sensing, which have the luxury to utilize hardware with high size, weight, and power (SWaP) resources. In this work, we develop and test a spectrum sensor for CubeSat radio applications. Given that CubeSat radios are inherently designed for low SWaP, they cannot implement the computationally expensive spectral correlation analyzer (SCA) algorithms for signal detection. To that end, our investigation focuses on the application of the SCA to square-root-raised-cosine (SRRC) pulse-shaped quadrature amplitude modulation (QAM) waveforms using a field-programmable gate array (FPGA). This model requires no prior knowledge of the radio-frequency (RF) channel. We show that this model can consistently and accurately detect the symbol rate and center frequencies of waveforms located in a spectrum.

cubesat↗

NASA NTRS1982

On the inversion of block tridiagonals without storage constraints

A strategy was developed to permit trade-offs between the number of floating point operations required and the storage requirements for the solution of certain difference problems, such as block tridiagonal systems of equations. This is done by recomputing some intermediate results instead of storing them. Reducing the storage to the square root of the current requirement roughly doubles the number of computations. Reducing the storage more than this tends to make the number of computations prohibitively large. In theory, if m is the order of each sub-matrix in the block tridiagonal matrix, one can solve any linear system with only 5m(2) + 1 temporary storage cells. In many cases m is a constant and quite small. For example, in solving a factored form of the three-dimensional Navier-Stokes equations, the size m of the block tridiagonals is 5. This method lends itself to efficient use on computers with parallel processing or vector processing architectures. On these computers the larger number of floating point operations is more than offset by the decrease in I/O and the increased percentage of vector operations made possible by this algorithm.

Merriam, M. L.↗

NASA NTRS2010

Orbital Gravity Gradiometry Beyond GOCE: Mission Concepts

Significant advances in the technologies needed for space-based cryogenic instruments have been made in the last decade, including cryocoolers, spacecraft architectures and cryogenic amplifiers. These enable considerably more complex instruments to be put into orbit for long-duration missions. One such instrument is the Superconducting Gravity Gradiometer (SGG) developed by Paik, et al. A magnetically levitated version is under consideration for a follow-on mission to GRACE (Gravity Recovery and Climate Experiment) and GOCE (Gravity field and steady-state Ocean Circulation Explorer). With its inherently greater rejection of common mode accelerations and ability to cancel the coupling of angular accelerations into the gradient signal, the SGG can achieve [an accuracy of] 0.01 milli-Eotvos (gravitational gradient of the Earth) divided by the square root of frequency in hertz, with requirements for attitude control that can be met with existing spacecraft. In addition, the use of a cryocooler for cooling the instrument will alleviate the previously severe constraint on mission lifetime imposed by the use of superfluid helium,. enabling mission durations in the 5-10 year range. Studies are underway to determine requirements for orbit (polar versus sun-synchronous), altitude (which affects spacecraft drag), instrument temperature and stability, cryocooler vibration control, and control and readout electronics. These will be used to determine the SGG's sensitivity and ultimate resolution for gravity recovery. This paper will discuss preliminary instrument and spacecraft design, and toplevel mission requirements.

Shirron, Peter J.↗

NASA NTRSDate not supplied

Creating Formal Characterizations of Routine Contingency Management in Commercial Aviation

The identification, modelling, and analysis of root causes of accidents and incidents dominate conventional safety management approaches. However, the effect of humans’ safety-producing behavior on the overall resilience of the system is often neglected. Additionally, emerging aviation markets are giving rise to concepts of operation, such as urban air mobility and optionally piloted air cargo operations, that are leading to a shift in locus of control between humans and automation. Without an understanding of the human contribution to safety, it is difficult to assess the effects of these novel role allocations on overall system safety. In this work, safety-producing behaviors are identified and abstracted into resilient performance strategies. Production rules that encapsulate these strategies are then generated and classified in the Soar cognitive architecture. The strategies are then applied to a remotely-operated air cargo example to demonstrate how safe learning is facilitated. The learned rules and strategies are then formally verified.

Safety Critical Systems↗

DOE OSTI2024

Frequency Response Improvement in a Standalone Small Hydropower Plant Using Battery Storage

This paper proposes a control architecture for frequency, current, and voltage control that facilitates using battery storage to improve the response of standalone small hydropower plants. The frequency controller uses rate-of-change of frequency and frequency-Watt-based generations to produce active power commands. The distinctive feature of the controller design is that it nicely integrates response to frequency change with constraints on frequency and state of battery to enable power injections. The current and voltage control scheme allows incorporating the frequency controller. The distinctive feature of this controller is that it incorporates a bounded integral control strategy that guarantees stability. Results on the stability of the hydropower plant with proposed scheme are presented and robust ways to choose the controller gains are investigated via root locus analysis. In conclusion, simulations performed show that: the hydropower plant response is significantly improved with battery storage using the proposed scheme; the load carrying capability of the hydropower plant is significantly improved with battery storage; the proposed scheme has the capability to recharge the battery; and the proposed control scheme gives improved performance.

13 HYDRO ENERGY↗

NASA NTRS2018

Pterodactyl: Integrated Control Design for Precision Targeting of Deployable Entry Vehicles

Deployable Entry Vehicles (DEVs) enable in-situ scientific exploration at destinations with atmospheres across the solar system. Because they stow in a compact form and deploy only when ready to enter the atmosphere, DEVs relax the volume constraint imposed by rigid aeroshells. This work seeks to do for a DEV what the Wright Brothers did to propel modern day aviation: develop the guidance and control (G&C) methods that will make maneuvering and precision landing of DEV a reality. The Pterodactyl project objective is to deliver an integrated G&C methodology for a DEV, based on a detailed analysis that utilizes a Multi-disciplinary, Design, Analysis and Optimization (MDAO) framework. The current state-of-the-art for blunt body entry, G&C is rooted in the precision landing of vehicles such as Mars Science Laboratory (MSL) and Apollo, which used a propulsive reaction control system (RCS) to steer. Recent research has taken a particular interest in non-propulsive control for DEVs, including direct force control (angle of attack modulation via control surfaces or mass movement) and drag modulation (discrete change in ballistic coefficient). Using the MDAO framework that includes a guidance and control model to explore multiple control concepts for a DEV will shed light on the best design approach for these vehicles. In Pterodactyl, we will complete this study for a novel DEV concept, and then we will fabricate a functional prototype to help validate the design. The project is expected to down-select to a final control architecture by the end of 2018, and complete fabrication of the prototype by the end of 2019.The DEV chosen for detailed study in this project is the Adaptable Deployable Entry and Placement Technology (ADEPT). ADEPT uses a revolutionary 3D-woven carbon fabric that is foldable, can serve as primary structure, and can survive the extreme heating environment of atmospheric entry. The specific configuration of ADEPT under investigation is called Lifting Nano-ADEPT (LNA). LNA is designed for secondary payloads missions that require precision landing either for scientific objectives at a target destination or for payload recovery at Earth.The MDAO framework being created through this research, called COBRA-Pt (Composite Beam Roll-Up Solar Array-Prototype), will combine three critical elements of the system design: a guidance algorithm with Monte Carlo, a parametric control model, and vehicle geometry details. Novel control models being studied are deployable aerodynamic surfaces as well as shape morphing. These concepts will be compared at the system level with a more traditional propulsive RCS by comparing several key performance parameters. Upon completion of the design study, a functional prototype of LNA will be fabricated that will include the integration of guidance software and relevant control actuators. We expect this study will provide critical data that could feed into the development of an Earth-based flight test of LNA. The COBRA-Pt framework will provide a modular system by which to study any DEV concept in any atmosphere.

Smith, Brandon↗

DOE OSTI2024

Radio Frequency Spectrum Audit to Inventory Private Cellular Base Station Infrastructure

The ever-changing cellular communication landscape makes it difficult to identify, map, and localize cellular base stations. Localizing cellular base stations provides various advantages, including information security, cybersecurity, spectrum management, and interference detection. For example, the MITRE ATT&CK® (Adversarial Tactics, Techniques, and Common Knowledge architecture) [1] and Common Attack Pattern Enumeration and Classification [2] emphasize the importance of being able to minimize the cyber security threat presented by unregulated private cellular base stations (PCBS). The majority of published research looks at the malicious use of PCBSs and focuses on using data retrieved from user equipment (UE), data obtained from an application on the UE, or data shared between the UE and a mobile network to locate it. This innovative strategy, however, focuses on the passively discovered uniqueness of radio frequency (RF) transmissions from commercial cellular infrastructure received in a designated monitoring position (DMP).

42 ENGINEERING↗

NASA NTRS2006

Fault Management Techniques in Human Spaceflight Operations

This paper discusses human spaceflight fault management operations. Fault detection and response capabilities available in current US human spaceflight programs Space Shuttle and International Space Station are described while emphasizing system design impacts on operational techniques and constraints. Preflight and inflight processes along with products used to anticipate, mitigate and respond to failures are introduced. Examples of operational products used to support failure responses are presented. Possible improvements in the state of the art, as well as prioritization and success criteria for their implementation are proposed. This paper describes how the architecture of a command and control system impacts operations in areas such as the required fault response times, automated vs. manual fault responses, use of workarounds, etc. The architecture includes the use of redundancy at the system and software function level, software capabilities, use of intelligent or autonomous systems, number and severity of software defects, etc. This in turn drives which Caution and Warning (C&W) events should be annunciated, C&W event classification, operator display designs, crew training, flight control team training, and procedure development. Other factors impacting operations are the complexity of a system, skills needed to understand and operate a system, and the use of commonality vs. optimized solutions for software and responses. Fault detection, annunciation, safing responses, and recovery capabilities are explored using real examples to uncover underlying philosophies and constraints. These factors directly impact operations in that the crew and flight control team need to understand what happened, why it happened, what the system is doing, and what, if any, corrective actions they need to perform. If a fault results in multiple C&W events, or if several faults occur simultaneously, the root cause(s) of the fault(s), as well as their vehicle-wide impacts, must be determined in order to maintain situational awareness. This allows both automated and manual recovery operations to focus on the real cause of the fault(s). An appropriate balance must be struck between correcting the root cause failure and addressing the impacts of that fault on other vehicle components. Lastly, this paper presents a strategy for using lessons learned to improve the software, displays, and procedures in addition to determining what is a candidate for automation. Enabling technologies and techniques are identified to promote system evolution from one that requires manual fault responses to one that uses automation and autonomy where they are most effective. These considerations include the value in correcting software defects in a timely manner, automation of repetitive tasks, making time critical responses autonomous, etc. The paper recommends the appropriate use of intelligent systems to determine the root causes of faults and correctly identify separate unrelated faults.

O'Hagan, Brian↗

DOE OSTI2025

Bayesian Optimized Deep Ensemble for Uncertainty Quantification of Deep Neural Networks: a System Safety Case Study on Sodium Fast Reactor Thermal Stratification Modeling

Deep neural networks (DNNs) are increasingly important to scientific computing and engineering system simulations. Accurate uncertainty quantification (UQ) for DNNs is critical in safety-sensitive engineering domains. Traditional Deep Ensemble (DE) methods, while easy to implement, frequently suffer from poorly calibrated uncertainty estimates and limited predictive accuracy due to reliance on fixed architectures with varied weight initializations. To address these issues, we introduce a workflow that combines Bayesian Optimization (BO) and DE. The workflow is modular, scalable, and integrates parallel BO initialized with Sobol sequences to individually optimize the hyperparameters of each ensemble member. This method enhances ensemble diversity, improves predictive accuracy, and provides reliable uncertainty estimates. We evaluate the proposed BODE approach in a sodium fast reactor thermal stratification modeling case study, where we used a densely connected convolutional neural network to predict turbulent viscosity during the reactor transient with consideration of data noise. We benchmark its performance against several optimization approaches, including baseline deep ensemble, evolutionary algorithm-optimized ensemble, ensemble formed via random search combined with greedy selection, and a BO ensemble using random initialization. Here, our results demonstrate superior performance of the developed BODE approach. In noise-free scenarios, BODE notably reduces incorrect aleatoric uncertainty and significantly enhances predictive accuracy. Under conditions of 5% and 10% Gaussian noise, BODE adaptively quantifies uncertainty proportional to data noise, achieving up to an 80% reduction in root mean square error compared to baseline methods and producing well-calibrated prediction intervals.

Bayesian optimization↗

NASA NTRS1987

Wafer level reliability for high-performance VLSI design

As very large scale integration architecture requires higher package density, reliability of these devices has approached a critical level. Previous processing techniques allowed a large window for varying reliability. However, as scaling and higher current densities push reliability to its limit, tighter control and instant feedback becomes critical. Several test structures developed to monitor reliability at the wafer level are described. For example, a test structure was developed to monitor metal integrity in seconds as opposed to weeks or months for conventional testing. Another structure monitors mobile ion contamination at critical steps in the process. Thus the reliability jeopardy can be assessed during fabrication preventing defective devices from ever being placed in the field. Most importantly, the reliability can be assessed on each wafer as opposed to an occasional sample.

Root, Bryan J.↗

DOE OSTI2025

Forecasting Multi-Step-Ahead Street-Scale Nuisance Flooding using a seq2seq LSTM Surrogate Model for Real-Time Application in a Coastal-Urban City

In coastal-urban cities facing an elevated risk of nuisance flooding (by rain and tide) due to increased heavy rainfall, sea level rise, urbanization, and aging drainage systems, real-time flood forecasting at the street-scale can provide useful information to transportation decision-makers. Physics-Based Models (PBMs) that offer high accuracy come with high computational runtimes and costs that limit their application for real-time flood forecasting. To address this challenge, Machine Learning (ML) surrogate models trained from PBMs have been proposed to provide street-scale flood forecasts. Previous related studies have focused on using Long Short-Term Memory (LSTM) architectures to model hourly flood depth on streets. While LSTM models can capture input sequences effectively, they fall short in accurately preserving output sequences, limiting their suitability for multi-step-ahead forecasts. The seq2seq LSTM architecture offers a key advantage here by capturing the full sequence of input–output, making it potentially more suitable for multi-step-ahead flood forecasts compared to traditional LSTM models. However, seq2seq LSTM has not been tested for street-scale flood forecasting, particularly for rapidly fluctuating nuisance flooding events which require special attention to its temporal sequences. Hence, in this study, we applied the seq2seq LSTM model to explore multi-step-ahead street-scale nuisance flooding and compared its results to the traditional LSTM model as a benchmark model. LSTM and seq2seq LSTM surrogate models were applied to 22 flood-prone streets in Norfolk, Virginia, as a case study with a 4-hr (short-term) and 8-hr (long-term) lead time. The models were trained with environmental (rainfall and tide) and topographic (elevation, Topographic Wetness Index, and Depth-To-Water) features along with PBM-derived water depths for different storm events. The results demonstrated satisfactory performance of both LSTM and seq2seq LSTM surrogate models throughout the forecast period compared to the PBM. However, the seq2seq LSTM showed lower Mean Absolute Error (MAE)/ Root Mean Square Error (RMSE) and higher Nash–Sutcliffe Efficiency (NSE)/ correlation than the LSTM across most lead times, particularly for long-term forecasting due to its supremacy in handling both input–output sequences together, which is missing in the traditional LSTM. For example, in the long-term, the average RMSE ranges were 0.0268–0.0373 m for LSTM and 0.0226–0.0319 m for seq2seq LSTM, while in the short-term, they were 0.0263–0.0293 m and 0.0261–0.0283 m, respectively. Additionally, while both models exhibited similar performance in distinguishing flooded and non-flooded streets for flood depth ≥ 0.1 m, the seq2seq LSTM model demonstrated superior performance for higher flood depths (such as ≥ 0.2 m and ≥ 0.3 m). Once trained, inference took only 0.09 to 0.11 s (short-term) and 0.30 to 0.35 s (long-term) per storm event for the 22 streets, making the application highly suitable for real-time decision-making during nuisance flood events.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2020

Shape Validation and RF Performance of Inflatable Antennas

Inflatable aperture antennas are an emerging technology that is being investigated for potential use in science and exploration missions. In particular, for missions to Mars and beyond, large deployable aperture antennas can provide the antenna gain required for high data rate communications, where the necessary antenna diameter exceeds the available volume of typical launch vehicle platforms. As inflatable aperture antennas have not been proven fully qualified for space missions, the author's Master's Thesis assessed the Ruze equation in characterizing this antenna technology. Inflatable aperture antennas do not follow a parabolic shape, and so the Ruze equation is not applicable due to the macroscopic shape errors of this technology. Therefore, geometric evaluations of the surface profile cannot simply correlate antenna gain degradation with the root-mean-square shape error with a parabolic surface. Consequently, the focus of this work was to derive an accurate mathematical model of an inflatable aperture antenna in order to characterize its Radio Frequency (RF) performance. Calculus of Variations methodologies were used to derive the surface profile shape of the inflatable aperture antenna. Physical Optics techniques were used to generate the antenna pattern profile. Validation testing of the predicted inflatable antenna shape model was performed through use of Laser Radar metrology measurements on an inflatable test article. Assessments of the RF performance of the inflatable aperture antenna, compared with nominally shaped paraboloidal antennas, were obtained through simulations of both technologies using a common diameter, depth, and arc length. Assessments of the RF performance of the inflatable aperture antenna was also performed against itself for changes in distance of the antenna feed location in the axial direction. Whereas the Ruze equation is limited to assessing gain reduction, this effort will also assess beam spreading and first side lobe angle and magnitude. The ability to characterize the RF response of this antenna will provide for an improved understanding of this technology. The accurate representation of the shape of this type of antenna technology will help to identify the most appropriate ways in which this technology could be utilized in planning future communication architectures for NASA missions to Mars and beyond.

Welch, Bryan W.↗

NASA NTRSDate not supplied

Segmented Solid Surface Reflector Concentrically Stacked With Tubular Shape Memory Composite Hinges

A new architecture for solid surface reflector antennas scalable to sizes greater than 10 m is presented. The design uses compact, light, and simple advanced deployable structures to create sub-reflectors that can be assembled in space into larger units using a robotic arm. The seven-panel hexagonal sub-reflector is divided into hexagonal panels that stack concentrically and vertically. The central panel is connected to each side panel on the back side by a pair of tubular shape memory composite hinges that enable the required deployment kinematics with controlled dynamics. A secondary mechanism closes the interpanel gap. The focus of the paper is on the development of the sub-reflector elements, namely the tubular hinges that use embedded heaters and sensors for triggering and control, the actuation mechanisms, and the lightweight sandwich construction reflector panels. A parametric study using finite element analyses was conducted to assess how design features of the hinge affect its stowage and deployment dynamics. The preliminary component fabrication and testing results for the two-panel assembly breadboard model are outlined. Finally, the results of the test campaign with the brassboard reflector model are presented. A comparison of deployed reflector surface deviation between the measured surface after the stowage and deployment process and the pre-test scans and the nominal surface revealed root mean square errors of less than 1 mm, as required by X-band radiofrequency transmission.

gravity offloading↗

NASA NTRSDate not supplied

Segmented Hexagonal Antenna Reflector Concentrically Stacked Using Shape Memory Composite Tubular Hinges

gravity offloading methods↗