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This work will gather real-world data on the performance and potential industry impact on laboratory ventilation control of a new low-cost, open-source sensor that reports important metrics of the laboratory environment. A small network of sensors will be installed at an NREL laboratory facility.
An inertial measurement unit accumulates the instantaneous specific force applied to the sensor over a small window of time. Importantly, this accumulation occurs in the sensor’s frame, yet the specific force must be mathematically integrated in a different navigation frame, and these two frames may be rotating with respect to each other. Consequently, a correction is needed to not only account for the frame difference but also for the time variation in the frame difference. Many references provide derivations of this correction [1], but the derivation is often abbreviated, and important assumptions are sometimes left unstated. This memo addresses this gap and provides a clear derivation of the specific force transform with all assumptions specifically stated. This derivation is specific to the Earth-centered, Earth-fixed navigation frame, but, hopefully, the derivation is sufficiently clear that readers can apply it to other navigation frames. Generally, notation follows the same format as described in both [1, 2].
Thin-film sensors for measuring flow velocities in terms of times of flight are undergoing development. These sensors are very small and can be mounted flush with surfaces of airfoils, ducts, and other objects along which one might need to measure flows. Alternatively or in addition, these sensors can be mounted on small struts protruding from such surfaces for acquiring velocity measurements at various distances from the surfaces for the purpose of obtaining boundary-layer flow-velocity profiles. These sensors are related to, but not the same as, hot-wire anemometers. Each sensor includes a thin-film, electrically conductive loop, along which an electric current is made to flow to heat the loop to a temperature above that of the surrounding fluid. Instantaneous voltage fluctuations in segments of the loop are measured by means of electrical taps placed at intervals along the loop. These voltage fluctuations are caused by local fluctuations in electrical resistance that are, in turn, caused by local temperature fluctuations that are, in turn, caused by fluctuations in flow-induced cooling and, hence, in flow velocity. The differential voltage as a function of time, measured at each pair of taps, is subjected to cross-correlation processing with the corresponding quantities measured at other pairs of taps at different locations on the loop. The cross-correlations yield the times taken by elements of fluid to travel between the pairs of taps. Then the component of velocity along the line between any two pairs of taps is calculated simply as the distance between the pairs of taps divided by the travel time. Unlike in the case of hot-wire anemometers, there is no need to obtain calibration data on voltage fluctuations versus velocity fluctuations because, at least in principle, the correlation times are independent of the calibration data.
Improved in-situ meteorological measurements are needed for monitoring the weather and climate of the terrestrial and Martian atmospheres. We have initiated a program to assess the feasibility and utility of micro-sensors for precise in-situ meteorological measurements in these environments. Sensors are being developed for measuring pressure, temperature, wind velocity, humidity, and aerosol amounts. Silicon micro-machining and large scale integration technologies are being used to make sensors that are small, rugged, lightweight, and require very little power. Our long-term goal is to develop very accurate miniaturized sensors that can be incorporated into complete instrument packages or 'micro weather stations,' and deployed on a variety of platforms. If conventional commercially available silicon production techniques can be used to fabricate these sensor packages, it will eventually be possible to mass-produce them at low cost. For studies of the Earth's troposphere and stratosphere, they could be deployed on aircraft, dropsondes, radiosondes, or autonomous surface stations at remote sites. Improved sensor accuracy and reduced sensor cost are the primary challenges for these applications. For studies of the Martian atmosphere, these sensor packages could be incorporated into the small entry probes and surface landers that are being planned for the Mars Environmental SURvey (MESUR) Mission. That decade-long program will deploy a global network of small stations on the Martian surface for monitoring meteorological and geological processes. Low mass, low power, durability, large dynamic range and calibration stability are the principal challenges for this application. Our progress on each of these sensor types is presented.
The characteristics of silicon pressure sensors with an ultra-small diaphragm are described. The pressure sensors utilize rectangular diaphragm as small as 0.0127 x 0.0254 cm and a p-type Wheatstone bridge consisting of diffused piezoresistive elements, 0.000254 cm by 0.00254 cm. These sensors exhibit as high as 0.5 MHz natural frequency and 1 mV/V/psi pressure sensitivity. Fabrication techniques and high frequency results from shock tube testing and low frequency comparison with microphones are presented.
Pulses of narrow line-width optical photons can be used to calibrate and test sub-2 eV full-width at half-maximum (FWHM) energy resolution transition-edge sensor (TES) microcalorimeters at low energies (<1 keV),where it is very challenging to obtain X-ray calibration lines comparable to (or narrower than) the detector resolution. This scheme depends on the ability to resolve the number of 3 eV photons in each pulse, which we have recently demonstrated up to photon numbers of about 300. AtLTD-18 we showed preliminary results obtained with this technique on a 0.25 eV baseline resolution TES microcalorimeter designed for the ultra-high-resolution sub-array of the Lynx mission. The line-shape was well described by a simple Gaussian. However, the difficulty of delivering photons to the small 46 μm square absorbers resulted in a large thermal crosstalk signal, whose random nature is expected to rapidly degrade the observed energy resolution towards higher photon numbers/energies. We have since improved the coupling between the optical fiber and the TES absorber and report here our current results.
Recently CMOS (complementary metal-oxide-semiconductor) sensors have progressed to a point where they may offer improved performance in imaging x-ray detection compared to the CCDs often used in x-ray satellites. We demonstrate x-ray detection in the soft x-ray band (250-1700 eV) by a commercially available back-illuminated Sony IMX290LLR CMOS sensor using the Advanced Photon Source at the Argonne National Laboratory. Additionally, while operating the device at room temperature, we measure energy resolutions (FWHM) of 47 eV at 250 eV and and 77 eV 1700 eV which are comparable to the performance of the Chandra ACIS and the Suzaku XIS. Furthermore, we demonstrate that the IMX290LLR can withstand radiation up to 17.1 krad, making it suitable for use on spacecraft in low earth orbit.
A parametric simulation tool for pixel sensors is presented. A realistic pixel response is simulated purely based on measurement input, without requiring detailed knowledge of the underlying manufacturing process. As such, it provides an efficient alternative to the use of Technology Computer-Aided Design simulations, which typically depend on proprietary process information. Due to its parametric approach, the package is fast and thus particularly useful for larger detector systems and high hit rate environments. This work presents measurements, simulation and its validation for the MALTA2 sensor. It is a small collection electrode monolithic active pixel sensor produced in the Tower 180 nm complementary metal-oxide-semiconductor imaging process. Modifications to the sensor’s periphery, mainly in the hit merger, are studied in order to optimize the performance for tracking and calorimetry. This optimization is of special interest as part of the MALTA3 sensor redesign in the 65 nm Tower Partners Semiconductor Co. process.
A predictive algorithm is used to determine, in near real time, the steady state response of a slow responding sensor such as hydrogen gas sensor of the type which produces an output current proportional to the partial pressure of the hydrogen present. A microprocessor connected to the sensor samples the sensor output at small regular time intervals and predicts the steady state response of the sensor in response to a perturbation in the parameter being sensed, based on the beginning and end samples of the sensor output for the current sample time interval.
The NASA-Ames Sensors 2000! Program has developed a small, compact, modular, programmable, sensor signal conditioning and measurement system, initially targeted for Life Sciences Spaceflight Programs. The system consists of a twelve-slot, multi-layer, distributed function backplane, a digital microcontroller/memory subsystem, conditioned and isolated power supplies, and six application-specific, physiological signal conditioners. Each signal condition is capable of being programmed for gains, offsets, calibration and operate modes, and, in some cases, selectable outputs and functional modes. Presently, the system has the capability for measuring ECG, EMG, EEG, Temperature, Respiration, Pressure, Force, and Acceleration parameters, in physiological ranges. The measurement system makes heavy use of surface-mount packaging technology, resulting in plug in modules sized 125x55 mm. The complete 12-slot system is contained within a volume of 220x150x70mm. The system's capabilities extend well beyond the specific objectives of NASA programs. Indeed, the potential commercial uses of the technology are virtually limitless. In addition to applications in medical and biomedical sensing, the system might also be used in process control situations, in clinical or research environments, in general instrumentation systems, factory processing, or any other applications where high quality measurements are required.
VfOx, which stands for “Venus Oxygen Fugacity” is the DAVINCI mission’s Student Collaboration Experiment (SCE); a small single- objective sensor used to measure the partial pressure of molecular oxygen in Venus’ lower atmosphere. Through the mission timeline, VƒOx will be designed, fabricated, tested, operated, and results analyzed by undergraduate and graduate students mentored by the DAVINCI team in partnership with Johns Hopkins University and other institutions. The simple principal of VƒOx is a ceramic O 2 sensor derived from common applications, utilizing diffusion of O -2 ions between a standard (PdO) inside the sensor and the target atmosphere measured by a mW level voltage that depends directly on the standard/sample fO 2 ratio. A 60-day environmental test of a prototype design of the sensor was conducted at the Glenn Extreme Environment Rig (GEER) from August to October of 2022, in which VƒOx (Fig. 1) was placed inside the experimental chamber (Fig. 2) and brought to Venus surface temperature (460 °C) and pressure (92 bar) conditions, in a Venus like atmosphere (96.5% CO 2 , 3.5% N 2 ) that included trace gases like SO 2 , maintained by occasional “boosts” of extra gas during the experimental run.
Temporally continuous snow depth estimates are vital for understanding changing snow patterns and impacts on permafrost in the Arctic. We train a random forest machine learning model to predict snow depth from variability in ground surface temperature. To our knowledge, this is the first time that small ground surface temperature sensors have been used to estimate snow depth. The model performs well at sites where the model was trained and at pan-arctic evaluation sites (RMSE <= 0.15 m). Small temperature sensors are cheap and easy-to-deploy, so this technique enables spatially distributed and temporally continuous snowpack monitoring to an extent previously infeasible. The model is flexible and can be applied to datasets retroactively to retrieve snow depth estimates at additional sites. This code package includes a *.joblib file of the trained random forest model and a *.ipynb file showing how to clean input data, train the random forest model, and apply the model.
Ground water table (GWT) depth and soil moisture (SM) have been monitored at several locations at the Point Reyes field site (Californian coastal grassland) from 2021 to 2024. Monitoring is still on-going and data may be added to this archive at later time. The SM data have been acquired using Teros 12 Meter soil moisture sensors placed at 10, 30, 60 and 90 cm depth at 5 locations along a small hillslope. These sensors also collect soil temperature and bulk conductance. In addition, some collocated sensors provide pore pressure and Photochemical Reflectance Index (PRI). The GWT depth has been inferred from various type of Onset pressure transducers. The pressure measurements have been corrected for atmospheric pressure variations and sensor position relative to the ground surface to infer GWT depth, as well as with RTK GPS data to infer GWT elevation. The GWT data have been acquired at 5 distinct locations from 2020 to 2024 with the sensors placed at about 4 m depth. In addition, GWT data has been acquired for the 2023-2024 period with sensors located in 1 m deep shallow wells installed near each deeper well. This data is intended to evaluate possibly different dynamic in shallow (perched) and deep aquifer. The datasets are all provided in csv format. Please note that the interpretation of the GWT data needs to be done with consideration of environmental and well characteristics at the site and uncertainty in various variables. For more information on GWT and SM data, please contact the author.
Reactive health monitoring strategies during events like the COVID-19 pandemic highlighted the need for predictive, threat-agnostic diagnostics that can detect both known diseases and novel chemical or biological threats. To address this, we investigated an optical biosensor as a breath volatile organic compound (VOC) analyzer, aiming to emulate biological olfaction. We assembled and validated the device with thin film metal coated substrate-based sensors. We immobilized small biological recognition elements on the substrates and delivered controlled concentrations of target VOCs. The sensor was irradiated with a visible laser and the sensor signal was recorded. We characterized the laser performance and tested 3 recognition elements for 2 VOCs with varying concentrations (1-100 ppm). We also evaluated enhancement of the signal using nanostructures on the metal film in comparison with planar film substrate. We demonstrated detecting ethanol reliably at concentrations as low as ~2 ppm along with preliminary detection of acetone (<100 ppm). We also found several unexpected factors that influence the sensor behavior that should be addressed to further refine the device’s performance. The nanostructures were, as expected, found to amplify the sensor signals. These findings demonstrate the feasibility of the optical bio-sensing modality for breath VOC monitoring at physiologically relevant levels. This positions LLNL to develop a low-cost, scalable, broad-spectrum health monitoring capability aligned with the Early Detection thrust of the Bioresilience Mission Focus Area and attract external funding.
Theoretical and design considerations as well as fabrication and experimental work involved in the development of high-frequency silicon pressure sensors with an ultra-small diaphragm are discussed. A sensor is presented with a rectangular diaphragm of 0.0127 cm x 0.0254 cm x 1.06 micron; the sensor has a natural frequency of 625 kHz and a sensitivity of 0.82 mv/v-psi. High-frequency results from shock tube testing and low-frequency (less than 50 kHz) comparison with microphones are given.
Systems of fixed-position radiation sensors can provide information that assists emergency responders following nuclear and radiological incidents. State, local, tribal, and territorial (SLTT) government agencies that implement systems of fixed-position sensors are faced with numerous decisions regarding sensor selection, quantity, and placement. To develop guidance on implementation of radiation detection systems, we simulated the release of radioactive material in an urban environment using a combination of three models: the Weather Research Forecasting (WRF), Quick Urban and Industrial Complex (QUIC), and Monte Carlo N-Particle (MCNP) models. We then evaluated the performance of several hypothetical sensor systems. The small number of simulations we conducted are not sufficient to generate definitive design guidance for radiation sensor systems, but we did identify trends that would be of interest to emergency planners. For a scenario that releases 1000 curies of Cs-137, radiation detectors were needed at 500-meter intervals to have a high likelihood of event detection and to estimate source location and plume detection. We also noted that optimal detector altitude varied with distance to the source. We recommend additional research in this area be conducted to support developing sensor placement guidelines that expand on a range of locations, isotopes, activity levels, and different weather conditions. Original simulation strategies included a range of environments, additional radioisotopes (Am241 and AmBe), and a larger selection of sensor types. These types of expansions would support SLTT guidance on sensor system recommendations.
NASA's Marshall Space Flight Center (MSFC) has, for the last ten years, developed various video-based sensors for use in automated docking systems. The latest generation of sensor will operate at rates of up to 100 Hz, determining the relative position (X, Y, and Z) and attitude (Roll, Pitch, and Yaw) between the sensor and a small 3-dimensional target, making it suitable for applications in robotic sensing. The Advanced Video Guidance Sensor (AVGS) is designed to track multiple targets at different ranges and determine the position and attitude of each one. The previous generation of video sensor, the Video Guidance Sensor (VGS), was flown twice on the Space Shuttle to test its performance on orbit. One of the tests performed was determining the relative positions and attitudes between the VGS and its target, which was moved to various positions using the Remote Manipulator System (RMS). The RMS position data and VGS measured data were analyzed after the flights, with good correlation between the position and attitude data of the two data sets. The test using the RMS gives a good idea of the ability of the use of the AVGS as a sensor for end-effector position and attitude determination.
The study of volcanoes is important for both purely scientific and human survival reasons. From a scientific standpoint, volcanic gas and ash emissions contribute significantly to the terrestrial atmosphere. Ash depositions and lava flows can also greatly affect local environments. From a human survival standpoint, many people live within the reach of active volcanoes, and therefore can be endangered by both atmospheric (ash, debris) toxicity and lava flow. There are many potential information sources that can be used to determine how to best monitor volcanic activity worldwide. These are of varying temporal frequency, spatial regard, method of access, and reliability. The problem is how to incorporate all of these inputs in a general framework to assign/task/reconfigure assets to monitor events in a timely fashion. In situ sensing can provide a valuable range of complementary information such as seismographic, discharge, acoustic, and other data. However, many volcanoes are not instrumented with in situ sensors, and those that have sensor networks are restricted to a relatively small numbers of point sensors. Consequently, ideal volcanic study synergistically combines space and in situ measurements. This work demonstrates an effort to integrate spaceborne sensing from MODIS (Terra and Aqua), ALI (EO-1), Worldview-2, and in situ sensing in an automated scheme to improve global volcano monitoring. Specifically, it is a "sensor web" concept in which a number of volcano monitoring systems are linked together to monitor volcanic activity more accurately, and this activity measurement automatically tasks space assets to acquire further satellite imagery of ongoing volcanic activity. A general framework was developed for evidence combination that accounts for multiple information sources in a scientist-directed fashion to weigh inputs and allocate observations based on the confidence of an events occurrence, rarity of the event at that location, and other scientists' inputs. The software framework uses multiple source languages and is a general framework for combining inputs and incrementally submitting observation requests/reconfigurations, accounting for prior requests. The autonomous aspect of operations is unique, especially in the context of the wide range of inputs that includes manually inputted electronic reports (such as the Air Force Weather Advisories), automated satellite-based detection methods (such as MODVOLC and GOESVOLC), and in situ sensor networks.