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At least 37 records · Page 2

A Self Contained Method for Safe and Precise Lunar Landing

The return of humans to the Moon will require increased capability beyond that of the previous Apollo missions. Longer stay times and a greater flexibility with regards to landing locations are among the many improvements planned. A descent and landing system that can land the vehicle more accurately than Apollo with a greater ability to detect and avoid hazards is essential to the development of a Lunar Outpost, and also for increasing the number of potentially reachable Lunar Sortie locations. This descent and landing system should allow landings in more challenging terrain and provide more flexibility with regards to mission timing and lighting considerations, while maintaining safety as the top priority. The lunar landing system under development by the ALHAT (Autonomous precision Landing and Hazard detection Avoidance Technology) project is addressing this by providing terrain-relative navigation measurements to enhance global-scale precision, an onboard hazard-detection system to select safe landing locations, and an Autonomous GNC (Guidance, Navigation, and Control) capability to process these measurements and safely direct the vehicle to this landing location. This ALHAT landing system will enable safe and precise lunar landings without requiring lunar infrastructure in the form of navigation aids or a priori identified hazard-free landing locations. The safe landing capability provided by ALHAT uses onboard active sensing to detect hazards that are large enough to be a danger to the vehicle but too small to be detected from orbit, given currently planned orbital terrain resolution limits. Algorithms to interpret raw active sensor terrain data and generate hazard maps as well as identify safe sites and recalculate new trajectories to those sites are included as part of the ALHAT System. These improvements to descent and landing will help contribute to repeated safe and precise landings for a wide variety of terrain on the Moon.

Paschall, Stephen C., II↗

Managing Cassini Safe Mode Attitude at Saturn

The Cassini spacecraft was launched on October 15, 1997 and arrived at Saturn on June 30, 2004. It has performed detailed observations and remote sensing of Saturn, its rings, and its satellites since that time. In the event safe mode interrupts normal orbital operations, Cassini has flight software fault protection algorithms to detect, isolate, and recover to a thermally safe and commandable attitude and then wait for further instructions from the ground. But the Saturn environment is complex, and safety hazards change depending on where Cassini is in its orbital trajectory around Saturn. Selecting an appropriate safe mode attitude that insures safe operation in the Saturn environment, including keeping the star tracker field of view clear of bright bodies, while maintaining a quiescent, commandable attitude, is a significant challenge. This paper discusses the Cassini safe table management strategy and the key criteria that must be considered, especially during low altitude flybys of Titan, in deciding what spacecraft attitude should be used in the event of safe mode.

Attitude Control↗

An all-electronic fail-safe for stimulated Brillouin scattering suppression

The mitigation of transverse stimulated Brillouin scattering (SBS) via phase modulation is mandatory to avoid damage in high-energy laser systems. A novel fail-safe system that indirectly monitors the optical bandwidth applied to suppress SBS by monitoring the input, reflected, and through rf power of the SBS-suppression lithium-niobate phase modulator is demonstrated. The fail-safe system has high sensitivity and reliability provided by optimized redundant circuits for power monitoring and fail-safe decision logic. Calibration of the fail-safe’s thresholds is straightforward. Furthermore, the fail-safe circuitry reacts within 45 ns to stop an incorrectly modulated pulse by blocking the propagation of an electronic timing trigger.

fail-safe↗

Eye-Safe 1.5 and 2.0 Micron Laser Power Conversion Using Metamorphic InGaAs Photovoltaic Devices

Laser power transmission at 1.5 and 2.0 microns are considered eye-safe up to 0.1 W/cm2 irradiance. Further, the atmospheric bands at these two wavelengths may provide the highest optical transmission through the atmosphere in hazy conditions. By slowly changing the lattice-constant of InGaAs with a Compositionally Graded Buffer (CGB), we have fabricated InGaAs photovoltaic (PV) devices over a wide range of bandgaps useful for multijunction concentrating photovoltaic devices, thermophotovoltaic devices, and Laser Power Converters (LPC). Here, we have demonstrated monochromatic power conversion of 1.5-micron light with an eye-safe efficiency of 39.8% at 0.1 W/cm2 with InGaAs devices lattice-matched to InP with an Antireflection Coating (ARC). We have also demonstrated 30.2% and 24.5% eye-safe LPC efficiency of metamorphic InGaAs devices grown on GaAs substrates using GaInP and AlGaAsP CGBs, respectively. Finally, we have demonstrated metamorphic InGaAs devices grown on InP and GaAs substrates that are estimated to have eye-safe LPC efficiencies at 2.0 microns of 27.4% and 20.9% respectively. The efficiencies of all these LPC devices continues to increase up to about 30-70 times the eye-safe irradiance.

eye-safe↗

Experimental Safe Extremum Seeking for Accelerators

Here, we demonstrate the recent designs of safe extremum seeking (Safe ES) on the 1-km-long charged particle accelerator at the Los Alamos Neutron Science Center (LANSCE). Safe ES is a modification of extremum seeking (ES) which, in addition to minimizing an analytically unknown cost, also employs a safety filter based on an analytically unknown control barrier function (CBF) safety metric. Tuning is necessitated by accelerators being large complex systems, with many drifting parameters due to thermal effects and degradation. At the same time, safe operation (the maintenance of state constraints) is crucial, as damage brings astronomical costs, both financially and in operation downtime. Our measured (but analytically unknown) safety metric is the beam current. We perform multivariable Safe ES on three accelerator applications, in which we adapt 4, 6, and 3 magnet strength parameters, respectively. Two of the three applications are for validated simulation models of beamlines at LANSCE: the first for the proton radiography (pRad) beamline of 800-MeV protons for spot size tuning; the second on a high-performance code, HPSim, for tuning the low-energy beam transport (LEBT) region that contains a beam of 750-keV protons. The third is an experimental tuning of the steering magnets in the LEBT at LANSCE.

43 PARTICLE ACCELERATORS↗

Integral Battery Power Limiting Circuit for Intrinsically Safe Applications

A circuit topology has been designed to guarantee the output of intrinsically safe power for the operation of electrical devices in a hazardous environment. This design uses a MOSFET (metal oxide semiconductor field-effect transistor) as a switch to connect and disconnect power to a load. A test current is provided through a separate path to the load for monitoring by a comparator against a preset threshold level. The circuit is configured so that the test current will detect a fault in the load and open the switch before the main current can respond. The main current passes through the switch and then an inductor. When a fault occurs in the load, the current through the inductor cannot change immediately, but the voltage drops immediately to safe levels. The comparator detects this drop and opens the switch before the current in the inductor has a chance to respond. This circuit protects both the current and voltage from exceeding safe levels. Typically, this type of protection is accomplished by a fuse or a circuit breaker, but in order for a fuse or a circuit breaker to blow or trip, the current must exceed the safe levels momentarily, which may be just enough time to ignite anything in a hazardous environment. To prevent this from happening, a fuse is typically current-limited by the addition of the resistor to keep the current within safe levels while the fuse reacts. The use of a resistor is acceptable for non-battery applications where the wasted energy and voltage drop across the resistor can be tolerated. The use of the switch and inductor minimizes the wasted energy. For example, a circuit runs from a 3.6-V battery that must be current-limited to 200 mA. If the circuit normally draws 10 mA, then an 18-ohm resistor would drop 180 mV during normal operation, while a typical switch (0.02 ohm) and inductor (0.97 ohm) would only drop 9.9 mV. From a power standpoint, the current-limiting resistor protection circuit wastes about 18 times more power than the switch and the inductor configuration. In the fault condition, both the resistor and the inductor react immediately. The resistor reacts by allowing more current to flow and dropping the voltage. Initially, the inductor reacts by dropping the voltage, and then by not allowing the current to change. When the comparator detects the drop in voltage, it opens the switch, thus preventing any further current flow. The inductor alone is not sufficient protection, because after the voltage drop has settled, the inductor would then allow the current to change, in this example, the current would be 3.7 A. In the fault condition, the resistor is flowing 200 mA until the fuse blows (anywhere from 1 ms to 100 s), while the switch and inductor combination is flowing about 2 A test current while monitoring for the fault to be corrected. Finally, as an additional safety feature, the circuit can be configured to hold the switch opened until both the load and source are disconnected.

Burns, Bradley M.↗

Safe Haven Configurations for Deep Space Transit Habitats

Throughout the human space flight program there have been instances where systems failures resulting in smoke, fire, and pressure loss have occurred onboard space vehicles, putting crews at risk for loss of mission and loss of life. In most instances the missions have been in Low-Earth-Orbit (LEO) or Earth-Moon vicinity, with access to multiple volumes that could be used to quickly seal off the damaged module or access escape vehicles for return to Earth. For long duration missions beyond LEO, including Mars transit missions of about 1100 days, the mass penalty for multiple volumes and operating in an environment where a quick return will not be possible have been concerns. In 2016, a study was done to investigate a variety of dual pressure vessel configurations for habitats that could protect the crew from these hazards. It was found that with a modest increase in total mass it should be possible to provide significant protection for the crew. Several configurations were considered that either had a small safe haven to provide 30-days to recover, or a full duration safe haven using two equal size pressure vessel volumes. The 30-day safe haven was found to be the simplest, yielding the least total mass impact but still with some risk if recovery is not possible during that timeframe. The full duration safe haven was the most massive option but provided the most robust solution. This paper provides information on the various layouts developed during the study and provides a discussion of the findings for implementing a safe haven in future habitat designs.

Smitherman, David↗

Safe Haven Configurations for Deep Space Transit Habitats

Throughout the human space flight program there have been instances where smoke, fire, and pressure loss have occurred onboard space vehicles, putting crews at risk for loss of mission and loss of life. In every instance the mission has been in Low-Earth-Orbit (LEO) with access to multiple volumes that could be used to quickly seal off the damaged module or escape vehicles for a quick return to Earth. For long duration space missions beyond LEO, including Mars transit missions of about 1000 days, the mass penalty for multiple volumes has been a concern as has operating in an environment where a quick return will not be possible. In 2016 a study was done to investigate a variety of dual pressure vessel configurations for habitats that could protect the crew from these hazards. It was found that for a modest increase in total mass it should be possible to provide significant protection for the crew. Several configurations were developed that either had a small safe haven to provide 30-days to recover, or a full duration safe haven using two equal size pressure vessel volumes. The 30-day safe haven was found to be the simplest, yielding the least total mass impact but still with some risk if recovery is not possible during that timeframe. The full duration safe haven was the most massive option but provided the most robust solution. This paper provides information on the various layouts considered in the study and provides a discussion of the findings for implementing a safe haven in future habitat designs.

Smitherman, David↗

Modeling Spacecraft Safe Mode Events

Spacecraft enter a ‘safe mode’ to protect the vehicle when a potentially harmful anomaly occurs. This minimally functioning state isolates faults, establishes contact with Earth, and orients the vehicle into a power positive attitude until operators intervene. Though ‘safings’ are inherently unpredictable, mission teams build in time margin during operations to determine root causes and restore functionality. Planning and managing this margin is both critical and enabling on mission architectures dependent on near-continuous operability – such as a low-thrust electric propulsion mission. To better quantify the occurrences and severity of safe mode anomalies, the Jet Propulsion Laboratory (JPL) has assembled a database of safings from past and active missions. Currently nearly 240 records are captured from 21 beyond-Earth missions, stemming from a collaboration between teams at JPL, Ames Research Center, Goddard Space Flight Center, and the Johns Hopkins University Applied Physics Laboratory. This paper discusses the event database, explores a statistical approach in modeling the occurrences and severity of safing events, presents a simulation technique, and details recommendations and future work to benefit future concepts.

Nicholas, Austin↗

Hazard Boresight Relative Navigation for Safe Lunar Landing

In the area of planetary landing, hazard detection and avoidance is the act of driving a vehicle to a safe landing area using onboard resources. A hazard detection sensor is used to scan the terrain and these measurements are evaluated to determine where the safe landing sites are located. The selected site is generally not the same as the nominal target, so the vehicle must divert to the new site. This activity involves the interaction between several components, including a suite of onboard GNC algorithms that work together to efficiently choose and divert to a new site. This paper presents the Hazard Boresight Relative Navigation concept, which is a method that provides a common interface between the hazard scan, safe-site selection algorithm, size of the target-relative landing ellipse, divert offset distance and guidance targeting algorithm. After the safe-site is selected from the hazard scan, the original inertial target is replaced with a vehicle-relative target, which is initialized by a measurement from the hazard scan. The new target-relative position state is estimated over time in the navigation filter, and is fed to the guidance algorithm to perform the divert maneuver. In addition to detailing the Hazard Boresight Relative Navigation concept, this paper also presents some general landing terms that can be used in the greater discussion, as well as analysis on how to estimate and predict the vehicle footprint dispersion ellipse during flight, which is used in the safe-site selection algorithm.

Stephen R. Steffes↗

Hazard Boresight Relative Navigation for Safe Lunar Landing

In the area of planetary landing, hazard detection and avoidance is the act of driving a vehicle to a safe landing area using onboard resources. A hazard detection sensor is used to scan the terrain and these measurements are evaluated to determine where the safe landing sites are located. The selected site is generally not the same as the nominal target, so the vehicle must divert to the new site. This activity involves the interaction between several components, including a suite of onboard GNC algorithms that work together to efficiently choose and divert to a new site. This paper presents the Hazard Boresight Relative Navigation concept, which is a method that provides a common interface between the hazard scan, safe-site selection algorithm, size of the target-relative landing ellipse, divert offset distance and guidance targeting algorithm. After the safe-site is selected from the hazard scan, the original inertial target is replaced with a vehicle-relative target, which is initialized by a measurement from the hazard scan. The new target-relative position state is estimated over time in the navigation filter, and is fed to the guidance algorithm to perform the divert maneuver. In addition to detailing the Hazard Boresight Relative Navigation concept, this paper also presents some general landing terms that can be used in the greater discussion, as well as analysis on how to estimate and predict the vehicle footprint dispersion ellipse during flight, which is used in the safe-site selection algorithm.

Stephen Steffes↗

Trends in the administration of COVID-19 vaccines with other vaccines in the United States reported to V-safe during December 14, 2020—May 19, 2023

Introduction COVID-19 vaccines may be administered with other vaccines during the same healthcare visit. COVID-19 monovalent (Fall 2021) and bivalent (Fall 2022) vaccine recommendations coincided with annual seasonal influenza vaccination. Data describing the frequency of the co-administration of COVID-19 vaccines with other vaccines are limited. Methods We used V-safe, a voluntary smartphone-based U.S. safety surveillance system established by the CDC, to describe trends in the administration of COVID-19 vaccines with other vaccines reported to V-safe during December 14, 2020 – May 19, 2023. Results Of the 21 million COVID-19 vaccinations reported to V-safe, 2.2% (459,817) were administered with at least 1 other vaccine. Co-administration most frequently occurred during the first week of October 2023 (27,092; 44.1%). Most reports of co-administration included influenza vaccine (393,003; 85.5%). Co-administration was most frequently reported for registrants aged 6 months-6 years (4,872; 4.4%). Conclusion Reports of co-administration to V-safe peaked during October 2023, when influenza vaccination most often occurs, possibly reflecting increased opportunities for multiple vaccinations and greater acceptability of the co-administration of COVID-19 vaccine with other vaccines, especially influenza vaccine.

60 APPLIED LIFE SCIENCES↗

A Safe Haven Concept for the Common Habitat in Moon, Mars, and Transit Environments

The safe haven for the Common Habitat architectures, both the Deep Space Exploration Vehicle and the Moon/Mars surface basecamps, consists of the airlock, logistics modules, and in-space or surface pressurized rovers. These elements are repositioned to dock together and form a secondary habitable environment. The multiple elements that compose the safe haven and its ability to share utilities across docking ports give it multiple subsystem options to sustain the crew. In the safe haven configuration, the two logistics modules dock to the side hatches of the airlock outer chamber, one pressurized rover docks to the outermost airlock hatch, and the second pressurized rover docks to the first. This configuration provides no less than thirty days of habitation for the eight-person crew. It also allows the airlock inner chamber to be used for EVAs to both the exterior surface and the Common Habitat interior, which may have lost pressure during the event that triggered the need for a safe haven. These EVAs enable the crew to work to repair the habitat and restore habitation capability.

Base camp↗

SAFE-OCC: A novelty detection framework for Convolutional Neural Network sensors and its application in process control

Herein we present a novelty detection framework for Convolutional Neural Network (CNN) sensors that we call Sensor-Activated Feature Extraction One-Class Classification (SAFE-OCC). We show that this framework enables the safe use of computer vision sensors in process control architectures. Emergent control applications use CNN models to map visual data to a state signal that can be interpreted by the controller. Incorporating such sensors introduces a significant system operation vulnerability because CNN sensors can exhibit high prediction errors when exposed to novel (abnormal) visual data. Unfortunately, identifying such novelties in real-time is nontrivial. To address this issue, the SAFE-OCC framework leverages the convolutional blocks of the CNN to create an effective feature space to conduct novelty detection using a desired one-class classification technique. This approach engenders a feature space that directly corresponds to that used by the CNN sensor and avoids the need to derive an independent latent space. We demonstrate the effectiveness of SAFE-OCC via simulated control environments.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Toward active disruption avoidance via real-time estimation of the safe operating region and disruption proximity in tokamaks

This paper describes a real-time capable algorithm for identifying the safe operating region around a tokamak operating point. The region is defined by a convex set of linear constraints, from which the distance of a point from a disruptive boundary can be calculated. The disruptivity of points is calculated from an empirical machine learning predictor that generates the likelihood of disruption. While the likelihood generated by such empirical models can be compared to a threshold to trigger a disruption mitigation system, the safe operating region calculation enables active optimization of the operating point to maintain a safe margin from disruptive boundaries. The proposed algorithm is tested using a random forest disruption predictor fit on data from DIII-D. The safe operating region identification algorithm is applied to historical data from DIII-D showing the evolution of disruptive boundaries and the potential impact of optimization of the operating point. Real-time relevant execution times are made possible by parallelizing many of the calculation steps and implementing the algorithm on a graphics processing unit. Lastly, a real-time capable algorithm for optimizing the target operating point within the identified constraints is also proposed and simulated.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

A Statistical Simulation Approach to Safe Life Fatigue Analysis of Redundant Metallic Components

This paper introduces a dual active load path fail-safe fatigue design concept analyzed by Monte Carlo simulation. The concept utilizes the inherent fatigue life differences between selected pairs of components for an active dual path system, enhanced by a stress level bias in one component. The design is applied to a baseline design; a safe life fatigue problem studied in an American Helicopter Society (AHS) round robin. The dual active path design is compared with a two-element standby fail-safe system and the baseline design for life at specified reliability levels and weight. The sensitivity of life estimates for both the baseline and fail-safe designs was examined by considering normal and Weibull distribution laws and coefficient of variation levels. Results showed that the biased dual path system lifetimes, for both the first element failure and residual life, were much greater than for standby systems. The sensitivity of the residual life-weight relationship was not excessive at reliability levels up to R = 0.9999 and the weight penalty was small. The sensitivity of life estimates increases dramatically at higher reliability levels.

Matthews, William T.↗

Safe Upper-Bounds Inference of Energy Consumption for Java Bytecode Applications

Many space applications such as sensor networks, on-board satellite-based platforms, on-board vehicle monitoring systems, etc. handle large amounts of data and analysis of such data is often critical for the scientific mission. Transmitting such large amounts of data to the remote control station for analysis is usually too expensive for time-critical applications. Instead, modern space applications are increasingly relying on autonomous on-board data analysis. All these applications face many resource constraints. A key requirement is to minimize energy consumption. Several approaches have been developed for estimating the energy consumption of such applications (e.g. [3, 1]) based on measuring actual consumption at run-time for large sets of random inputs. However, this approach has the limitation that it is in general not possible to cover all possible inputs. Using formal techniques offers the potential for inferring safe energy consumption bounds, thus being specially interesting for space exploration and safety-critical systems. We have proposed and implemented a general frame- work for resource usage analysis of Java bytecode [2]. The user defines a set of resource(s) of interest to be tracked and some annotations that describe the cost of some elementary elements of the program for those resources. These values can be constants or, more generally, functions of the input data sizes. The analysis then statically derives an upper bound on the amount of those resources that the program as a whole will consume or provide, also as functions of the input data sizes. This article develops a novel application of the analysis of [2] to inferring safe upper bounds on the energy consumption of Java bytecode applications. We first use a resource model that describes the cost of each bytecode instruction in terms of the joules it consumes. With this resource model, we then generate energy consumption cost relations, which are then used to infer safe upper bounds. How energy consumption for each bytecode instruction is measured is beyond the scope of this paper. Instead, this paper is about how to infer safe energy consumption estimations assuming that those energy consumption costs are provided. For concreteness, we use a simplified version of an existing resource model [1] in which an energy consumption cost for individual Java opcodes is defined.

Navas, Jorge↗

Safe Manual Jettison

In space, the controlled release of certain cargoes is no less useful than the maritime jettisons from which they take their name but is also much more dangerous. Experience has shown that jettisons can be performed safely, but the process is complicated with the path to performing a jettison taking months or even years. In the background, time is also required to write procedures, train the crew, configure the vehicle, and many other activities. This paper outlines the current process used by the National Aeronautics and Space Administration (NASA) for manual jettisons, detailing the methods used to assure that the jettisons and the jettisoned objects are as safe as achievable and that the crew is adequately trained to be able to affect the safe jettison. The goal of this paper is not only to capture what it takes to perform safe jettisons in the near Earth environment but to extrapolate this knowledge to future space exploration scenarios that will likely have Extravehicular Activity (EVA) and International Partner (IP) interfaces.

Barton, Jay↗