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At least 487 records · Page 27

Three-Wavelength Approach for Aerosol-Cloud Discrimination in the Sage III/ISS Aerosol Extinction Dataset

The tropical upper troposphere and lower stratosphere (UTLS) region is dominated by aerosols and clouds affecting Earth’s radiation budget and climate. Thus, satellites’ continuous monitoring and identification of these layers is crucial for quantifying their radiative impact. However, distinguishing between aerosols and clouds is challenging, especially under the perturbed UTLS conditions during post-volcanic eruptions and wildfire events. Aerosol-cloud discrimination is primarily based on their disparate wavelength-dependent scattering and absorption properties. In this study, we use aerosol extinction observations in the tropical (15°N-15°S) UTLS from June 2017 to February 2021, available from the latest generation of the Stratospheric Aerosol and Gas Experiment (SAGE) instrument-SAGE III onboard the International Space Station (ISS) to study aerosols and clouds. During this period, the SAGE III/ISS provided better coverage over the tropics at additional wavelength channels (relative to previous SAGE missions) and witnessed several volcanic and wildfire events that perturbed the tropical UTLS. We explore the advantage of having an extinction coefficient at an additional wavelength channel (1550 nm) from the SAGE III/ISS in aerosol-cloud discrimination using a method based on thresholds of two extinction coefficient ratios, R1R1 (520 nm/1020 nm) and R2R2 (1020 nm/1550 nm). This method was proposed earlier by Kent et al. [Appl. Opt. 36, 8639 (1997) [CrossRef] ] for the SAGE III-Meteor-3M but was never tested for the tropical region under volcanically perturbed conditions. We call this method the Extinction Color Ratio (ECR) method. The ECR method is applied to the SAGE III/ISS aerosol extinction data to obtain cloud-filtered aerosol extinction coefficients, cloud-top altitude, and seasonal cloud occurrence frequency during the entire study period. Cloud-filtered aerosol extinction coefficient obtained using the ECR method revealed the presence of enhanced aerosols in the UTLS following volcanic eruptions and wildfire events consistent with the Ozone Mapping and Profiler Suite (OMPS) and space-borne lidar-Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP). The cloud-top altitude obtained from the SAGE III/ISS is within 1 km of the nearly co-located observations from OMPS and CALIOP. In general, the seasonal mean cloud-top altitude from the SAGE III/ISS events peaks during the December, January, and February months, with sunset events showing higher cloud tops than the sunrise events, indicating the seasonal and diurnal variation of the tropical convection. The seasonal altitude distribution of cloud occurrence frequency obtained from the SAGE III/ISS also agrees well with CALIOP observations within 10%. We show that the ECR method is a simple approach that relies on thresholds independent of the sampling period, providing cloud-filtered aerosol extinction coefficients uniformly for climate studies irrespective of the UTLS conditions. However, since the predecessor of SAGE III did not include a 1550 nm channel, the usefulness of this approach is limited to short-term climate studies after 2017.

Clouds Aerosols↗

Condition monitoring and anomaly detection in cyber-physical systems

The modern industrial environment is equipping myriads of smart manufacturing machines where the state of each device can be monitored continuously. Such monitoring can help identify possible future failures and develop a cost-effective maintenance plan. However, it is a daunting task to perform early detection with low false positives and negatives from the huge volume of collected data. This requires developing a holistic machine learning framework to address the issues in condition monitoring of high priority components and develop efficient techniques to detect anomalies that can detect and possibly localize the faulty components. This paper presents a comparative analysis of recent machine learning approaches for robust, cost-effective anomaly detection in cyber-physical systems. While detection has been extensively studied, very few researchers have analyzed the localization of the anomalies. We show that supervised learning outperforms unsupervised algorithms. For supervised cases, we achieve near-perfect accuracy of 98% (specifically for tree-based algorithms). In contrast, the best-case accuracy in the unsupervised cases was 63%—the area under the receiver operating characteristic curve (AUC) exhibits similar outcomes as an additional metric.

Marfo, William↗

Clinical Decision Support Project

As NASA plans for exploration missions into deep space, significant challenges are realized due to the distance from Earth. Beside the effects of microgravity and radiation exposure, the astronauts face the additional constraints of isolation, lack of resupply, increasingly difficult evacuation, and delayed and disrupted communication with ground-based medical care providers. These constraints require a paradigm shift from current medical care where crews rely on the real-time communications with ground-based medical care providers toward Earth-independent medical operations for astronaut medical care. Medical expertise and decision-making are ground-based for current International Space Station and planned Lunar missions. However, a deep space exploration crew will need to autonomously perform the detection, diagnosis, treatment, and prevention of medical conditions. One approach to provide Earth-independent medical operations is to augment the requisite knowledge, skills, and abilities (KSAs) of a time-constrained crew—operating under stressful conditions, combatting fatigue, and facing a potential medical crisis—with a robust clinical decision support system (CDSS). The CDSS is envisioned as an integrated, software-based tool deployed on a laptop computer or handheld device. The CDSS will assist the crew and ground support when interacting with knowledge/data bases (e.g. records, pharmacy, schedule), instrumentation (e.g. imaging, physiological monitoring devices), and habitat (e.g. wellness system, task performance system) and vehicle systems (e.g. environmental system, communication system). In addition, the human interface will employ a context-based approach that accounts for the crew’s situation. Thus, extraneous and clinically/operationally non-relevant information are reduced to avoid an increase in cognitive load. The framework of an ideal spaceflight CDSS is to include core and advanced analytical features that maintain a flexible platform for integrating new technology in the future. The Exploration Medical Capability (ExMC) Element of the Human Research Program (HRP) is expanding the boundaries of space medical systems to advance the care of astronauts on future exploration missions beyond low Earth orbit by actively identifying and testing next-generation medical care and crew health maintenance technologies. The Clinical Decision Support (CDS) project addressed ap Medical-701 within the Inflight Medical Conditions risk: “We need to increase inflight medical capabilities and identify new capabilities that (a) maximize benefit and/or (b) reduce “costs” on human system/mission/vehicle resources.” Though mass, volume, and power will face increasing constraints, the projected computational capabilities of spacecraft systems will increase exponentially as information technology advances in this decade and beyond. Hence, data, software, and computational resources will play an essential and synergistic role in maintaining crew health, wellness, and performance in deep space missions. The focus of the CDS project was to develop recommended requirements for an in-vehicle CDSS that acts as a ‘virtual assistant’ for delivering optimal health, performance, and medical care during exploration missions. In fiscal year 2022 (FY22), the CDS project was chartered to baseline and/or revise all CDS project related documentation and update the CDS project model to include the revised CDSS Concept of Operations, revised systems-based modeling language (SysML) activity diagrams, and baseline requirements. The focus of this presentation will be an overview of the CDS products and CDS model content.

Decision Support↗

Transition to Online Cable Insulation Condition Monitoring

Nuclear power plant cables were originally qualified for 40 year life and generally have not required specific test verification to assure service availability through the initial plant qualification period. However, license renewals to 60 and 80 years of operation require a cable aging management program that depends on some form of test and verification to assure fitness for service. Environmental stress (temperature, radiation, chemicals, water, and mechanical) varies dramatically within a nuclear power plant and, in some cases, cables have degraded and required repair or replacement before their qualified end-of-life period. In other cases, cable conditions have been mild and dependable cable performance confirmed to extend well beyond the initial qualified life. Most offline performance-based testing requires cables to be de-coupled and de-energized for specially trained technicians to perform testing. These offline tests constitute an expensive operational burden that limits the economic viability of nuclear power plants. Although initial investment may be higher, new online test practices are emerging as options or complements to offline testing that avoid or minimize the regularly scheduled offline test burden. These online methods include electrical and fiber-optic partial discharge measurement, spread spectrum time or frequency domain reflectometry, distributed temperature profile measurements, and local interdigital capacitance measurement of insulation characteristics. Introduction of these methods must be supported by research to confirm efficacy plus either publicly financed or market driven investment to support the start-up expense of cost-effective instrumentation to monitor cable condition and assure reliable operation. This work summarizes various online cable assessment technologies plus introduces a new cable motor test bed to assess some of these technologies in a controlled test environment.

Glass, Samuel W.↗

Leveraging FPGA Advantages for Quicker Data Processing for LBNF

The Long Baseline Neutrino Facility (LBNF) will deliver a 2.4 MW muon neutrino beam from Fermilab to the Deep Underground Neutrino Experiment (DUNE), requiring unprecedented precision in beamline alignment to achieve DUNE's neutrino oscillation measurement goals. Vertical misalignments of beamline components as small as 0.5 mm can contribute 6-7\% uncertainty in predicted neutrino flux, necessitating sub-0.1 mm alignment monitoring capabilities. The Horn Location Sensor (HLS) system employs frequency sweep interferometry (FSI) in a distributed hydrostatic leveling network to achieve the required precision under harsh radiation conditions up to 5000 kRad/year. Traditional FSI implementations suffer from laser sweep nonlinearities that degrade resolution and require computationally intensive post-processing corrections using gas reference cells. This work presents a real-time FPGA-based implementation of the HLS data acquisition and processing system using a sweep tracker interferometer for dynamic sweep linearization. The system utilizes a PYNQ-Z2 FPGA with programmable logic implementing parallel 16k-point FFT processing across four channels, synchronized by the sweep tracker signal to eliminate post-processing requirements. Spectral performance testing demonstrates significant improvements in peak sharpness compared to traditional fixed-frequency digitization. The FPGA implementation enables real-time displacement monitoring with processing speeds orders of magnitude faster than software-based approaches, essential for the operational requirements of LBNF's eventual distributed sensor network. This advancement in real-time FSI processing directly supports DUNE's precision neutrino physics program by providing the rapid feedback necessary for maintaining stringent beamline alignment tolerances during high-power beam operations.

Rossel, Jacob↗

Real-Time FPGA Implementation For Frequency Sweep Interferometry In The LBNF Complex

The Long Baseline Neutrino Facility (LBNF) will deliver a 2.4 MW muon neutrino beam from Fermilab to the Deep Underground Neutrino Experiment (DUNE), requiring unprecedented precision in beamline alignment to achieve DUNE's neutrino oscillation measurement goals. Vertical misalignments of beamline components as small as 0.5 mm can contribute 6-7\% uncertainty in predicted neutrino flux, necessitating sub-0.1 mm alignment monitoring capabilities. The Horn Location Sensor (HLS) system employs frequency sweep interferometry (FSI) in a distributed hydrostatic leveling network to achieve the required precision under harsh radiation conditions up to 5000 kRad/year. Traditional FSI implementations suffer from laser sweep nonlinearities that degrade resolution and require computationally intensive post-processing corrections using gas reference cells. This work presents a real-time FPGA-based implementation of the HLS data acquisition and processing system using a sweep tracker interferometer for dynamic sweep linearization. The system utilizes a PYNQ-Z2 FPGA with programmable logic implementing parallel 16k-point FFT processing across four channels, synchronized by the sweep tracker signal to eliminate post-processing requirements. Spectral performance testing demonstrates significant improvements in peak sharpness compared to traditional fixed-frequency digitization. The FPGA implementation enables real-time displacement monitoring with processing speeds orders of magnitude faster than software-based approaches, essential for the operational requirements of LBNF's eventual distributed sensor network. This advancement in real-time FSI processing directly supports DUNE's precision neutrino physics program by providing the rapid feedback necessary for maintaining stringent beamline alignment tolerances during high-power beam operations.

Rossel, A. Jacob [Fermilab; Unlisted]↗

Meshfree simulation and experimental validation of extreme thermomechanical conditions in friction stir extrusion

Abstract Friction stir extrusion (FSE) is a novel solid-phase processing technique that consolidates and extrudes metal powders, flakes, chips, or billets into high-performance parts by plastic deformation, which has the potential to save substantial processing time and energy. Currently, most studies on FSE are experimental and only a few numerical models have been developed to explain and predict the complex physics of the process. In this work, a meshfree simulation framework based on smoothed particle hydrodynamics (SPH) was developed for FSE. Unlike traditional grid-based methods, SPH is a Lagrangian particle-based method that can handle severe material deformations, capture moving interfaces and surfaces, and monitor the field variable histories explicitly without complicated tracking schemes. These aspects of SPH make it attractive for the FSE process, where in situ evolution of field variables is difficult to observe experimentally. To this end, a 3-D, fully thermomechanically coupled SPH model was developed to simulate the FSE of aluminum wires. The developed model was thoroughly validated by comparing the numerically predicted material flow, strain, temperature history, and extrusion force with experimental results for a certain set of process parameters. The validated SPH model can serve as an effective tool to predict and better understand the extreme thermomechanical conditions during the FSE process.

99 GENERAL AND MISCELLANEOUS↗

Electrodeposition in microgravity: Ground-based experiments

Electrodeposition was studied at one-hundreth g and compared with bench studies at 1 g. The low gravity was achieved during KC-135 aircraft parobolic flights. Flow in a simple cobalt cell (1 M CoSO4) operating under typical commercial conditions (10 to 20 mA/sq cm and 1 V) was monitored with a Schlieren optical system. Natural convection was absent at one-hundreth g. Quantitative comparisons on a cobalt cell with shielded electrodes using interferometry were carried out. Fringe shift differences indicate greater semi-infinite linear diffusion at 1 g than at one-hundreth g for cobalt. Since a shielded electrode operates under diffusion controlled conditions, no differences between 1 g and one-hundreth g would be expected. Similar comparisons on a shielded electrode copper cell were inconclusive. Bench codeposition experiments using polystyrene neutral buoyancy particles coupled with a shielded electrode cobalt cell were begun. Tracking of 12 micron particles showed no measurable difference between thermal/Brownian motion when the cell was operational or nonoperational. Initial experiments on codeposition quality showed a strong dependence upon cathode surface preparation in a shielded electrode configuration.

Riley, C.↗

Development of an optical sensor for measuring opacity changes in polyvinyl toluene scintillators

Polyvinyl toluene (PVT) based detectors are used in radiation portal monitors (RPMs) worldwide to detect the trafficking of illicit nuclear material. PVT scintillators, which are normally optically clear, have been observed to suffer internal fogging throughout their volume due to prolonged exposure to varying environmental conditions. These changes could lead to reduced performance for RPMs that utilize plastic scintillators. In this research, a proof of concept system, consisting of different color light emitting diodes (LEDs) and a single optical sensor (OS), were used to examine the change in light transmission through a PVT scintillator. This Optical Monitoring System (OMS), coupled with an environmentally exposed PVT detector, was tested in an environmental chamber where it was subjected to changes in temperature and humidity ranging from 55 °C at 100% relative humidity to –20 °C at 40% relative humidity. At temperatures below 10 °C, light transmission was reduced by 81% ± 8% for blue LEDs, 84% ± 5% for yellow LEDs, and 49% ± 4% for green LEDs. Similar reductions in detected light were not recorded when the OMS was tested with only air between the LEDs and OS. Therefore, the significant reductions in transmitted light were attributed to changes occurring within the PVT scintillator. These results indicate that a significant reduction in PVT opacity occurs due to wide environmental changes. A device such as the OMS could be used to track these changes and provide users an early indication that a portal monitor is suffering from reduced performance.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Accelerating Multiphase Simulations With Denoising Diffusion Model Driven Initializations

This study introduces a hybrid fluid simulation approach that integrates generative diffusion models with physics‐based simulations, aiming at reducing the computational costs of flow simulations while still honoring all the physical properties of interest. Pore‐scale simulations enhance our understanding of applications such as assessing hydrogen and storage efficiency in underground reservoirs. Nevertheless, they are computationally expensive and the presence of non‐unique solutions can require multiple simulations within a single geometry. To overcome the computational cost hurdle, we propose a method that couples generative diffusion models and physics‐based simulations. While training the data‐driven model, we simultaneously generate initial conditions and perform physics‐based simulations using these. This integrated approach enables us to receive real‐time feedback on a single compute node equipped with both CPUs and GPUs. By efficiently managing these processes within a single compute node, we can continuously monitor performance and halt training once the model meets the specified criteria. To test our model, we generate realizations in a real Berea sandstone fracture which shows that our technique is up to 4.4 times faster than commonly used flow simulation initializations.

36 MATERIALS SCIENCE↗

A hardware-in-the-loop (HIL) testbed for cyber-physical energy systems in smart commercial buildings

In recent years, there has been a growing trend toward the development of smart buildings that rely on cyber-physical systems (CPS) to optimize occupant comfort, safety, and energy efficiency. To ensure the reliable and efficient operation of CPS with designed control strategies, it is important to evaluate their performance under various scenarios before deploying them in the real world. This is where a Hardware-in-the-loop (HIL) testbed designed for studying sensor and control-related studies in smart buildings can be highly valuable. With the growing threat of cyber-attacks and physical faults targeting smart buildings, it is essential to ensure the security of building operations. A HIL testbed can emulate cyber-attack and physical fault scenarios, allowing researchers to develop and test threat detection and mitigation algorithms. This enables researchers to identify potential issues and optimize the algorithms in a safe and controlled environment before they are deployed in real-world settings, reducing the risk of failures that can negatively impact occupant comfort, safety, and energy efficiency. Therefore, this paper developed a HIL testbed designed for cyber-physical energy systems (e.g. buildings automation system (BAS)) in smart commercial buildings. The HIL testbed is comprised of a real-time building and Heating, Ventilation, and Air-Conditioning (HVAC) emulator using Modelica-based dynamic models, a set of BAS controllers, and a BAS computer server. The data generation capability of the HIL testbed is demonstrated by tracking normal and faulty operating data in the BAS, as well as monitoring detailed network traffic in the local BAS network. Here, this study further demonstrates the HIL testbed’s capability by conducting case studies on real-time physical fault and cyber-attack experiments using a Department of Energy (DOE) prototype commercial building. It is anticipated that the fully functional HIL testbed will be utilized for a variety of sensor and control-related studies, including but not limited to testing, developing, validating of different HVAC control strategies, fault detection & diagnosis, energy monitoring and analysis, cyber security study, etc.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Application of fuzzy logic to the control of wind tunnel settling chamber temperature

The application of Fuzzy Logic Controllers (FLC's) to the control of nonlinear processes, typically controlled by a human operator, is a topic of much study. Recent application of a microprocessor-based FLC to the control of temperature processes in several wind tunnels has proven to be very successful. The control of temperature processes in the wind tunnels requires the ability to monitor temperature feedback from several points and to accommodate varying operating conditions in the wind tunnels. The FLC has an intuitive and easily configurable structure which incorporates the flexibility required to have such an ability. The design and implementation of the FLC is presented along with process data from the wind tunnels under automatic control.

Gwaltney, David A.↗

Looking at Ozone From a New Angle: Shuttle Ozone Limb Sounding Experiment-2 (SOLSE-2)

The ozone layer above Earth is our planet's fragile sunscreen, protecting people, vegetation, and wildlife. NASA has been measuring ozone for more than 20 years by looking down, but SOLSE-2 will show that more information is available by looking at ozone from the side, at Earth's limb or atmospheric boundary. When the ozone layer is compromised, increased ultraviolet (UV) levels from the sun cause health problems ranging from severe sunburns to skin cancer and cataracts. A concerted global effort has been made to reduce or eliminate the production of chemicals that deplete ozone, but the ozone layer is not expected to recover for many decades because these chemicals can remain active in the atmosphere for up to 100 years. We know now that ozone monitoring needs to be focused in the lower stratosphere. The discovery of the ozone hole in 1985 demonstrated that very large changes in ozone were occurring in the lower stratosphere near 20 km, instead of the upper stratosphere as first expected, and where current ozone instruments are focused. Measuring ozone from a tangential perspective that is centered at the limb provides ozone profiles concentrated in the lower stratosphere. The first flight of SOLSE proved that this technique achieves the accuracy and coverage of traditional measurements, and surpasses the altitude resolution and depth of retrieval of conventional techniques. Results from the first flight convinced the science community to design the next generation ozone monitoring satellite based on SOLSE. The Ozone Mapping and Profiling Suite (OMPS) is currently being built for the NPOESS satellite. The primary objective of SOLSE-2 is to confirm the promising results of the first flight over a wider range of viewing conditions and spectral wavelengths. Sometimes a really hard problem can be solved when you look at it from a different angle! While scientists conduct research, protect yourself by observing the UV index and spend less unprotected time outdoors.

McPeters, Richard↗

Application of Smart Solid State Sensor Technology in Aerospace Applications

Aerospace applications require a range of chemical sensing technologies to monitor conditions in both space vehicles and aircraft operations. One example is the monitoring of oxygen. For example, monitoring of ambient oxygen (O2) levels is critical to ensuring the health, safety, and performance of humans living and working in space. Oxygen sensors can also be incorporated in detection systems to determine if hazardous leaks are occurring in space propulsion systems and storage facilities. In aeronautic applications, O2 detection has been investigated for fuel tank monitoring. However, as noted elsewhere, O2 is not the only species of interest in aerospace applications with a wide range of species of interest being relevant to understand an environmental or vehicle condition. These include combustion products such as CO, HF, HCN, and HCl, which are related to both the presence of a fire and monitoring of post-fire clean-up operations. This paper discusses the development of an electrochemical cell platform based on a polymer electrolyte, NAFION, and a three-electrode configuration. The approach has been to mature this basic platform for a range of applications and to test this system, combined with "Lick and Stick" electronics, for its viability to monitor an environment related to astronaut crew health and safety applications with an understanding that a broad range of applications can be addressed with a core technology.

Hunter, Gary W.↗

Update of S-NPP VIIRS Thermal Emissive Bands Radiometric Calibration Stability Monitoring Using the Moon

The Suomi-NPP VIIRS thermal emissive bands (TEB) are radiometrically calibrated on-orbit with reference to an onboard blackbody (BB) regularly operated at approximately 292.5 K. The calibration stability at other temperature ranges can be evaluated based on the observations of remote targets with stable thermal properties, such as the Moon. VIIRS has scheduled viewings of the Moon on a nearly monthly basis at a phase angle of nearly -51 degrees. In this study, the brightness temperatures (BT) of the lunar surface retrieved using the detector gain coefficients calibrated with the BB are trended to monitor the calibration stability of VIIRS TEB. Since the Lunar surface temperatures are spatially non-uniform and vary greatly with the photometric geometry, the BT trending must be based on the same regions of the Moon under the same solar illumination condition. Also, the TEB lunar images are always partially saturated because the highest lunar surface temperatures are beyond the dynamic range of all VIIRS TEB detectors. Therefore, a temporally invariant dynamic mask is designed to clip a fraction of the lunar images corresponding to the regions of the Moon that may saturate the detector at any lunar event. The BT of the remaining hottest pixels are then trended. Results show that, since the launch of VIIRS to mid-2016, the radiometric calibration of all TEB detectors has been stable within 0.4 K at the BT range of as high as 350 K.

Wang, Zhipeng↗

Diagnosing Hybrid Systems: a Bayesian Model Selection Approach

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

McIlraith, Sheila A.↗

Evapotranspiration-Based Irrigation Scheduling in Salinas Valley Vegetable Crops

Crop evapotranspiration (ETc) monitoring may support improved irrigation water management in California's Central Coast agricultural region. The CropManage (CM) web-application, developed and operated by the University of California, informs irrigation and nitrogen scheduling decisions made by growers and crop consultants. Daily weather conditions are accounted for by use of grass reference ET data imported from the California Dept. Water Resources. Satellite observations of crop development from NASA's Satellite Irrigation Management Support can be imported and used by CM to adjust crop phenology. A replicated irrigation trial was performed July-October 2018 to investigate yield response of drip-irrigated celery (Apium graveolens) to applied water volume, and to further calibrate CM for use in that crop. Water was uniformly applied by sprinklers to establish the crop, and CM was then used to guide surface drip irrigation treatments applied three times weekly at 50%, 75%, 100%, 125% and 150% of ETc replacement level. Nitrogen fertilizer totaling 380 kg/ha was applied through the drip system generally once per week. Treatments were evaluated for commercial yield 85 and 93 days after transplanting (DAT). The 100% ETc treatment yielded 83 Mg/ha 93 DAT, which was 10 Mg/ha higher than the reported regional average yield in 2017. The 100% treatment received a seasonal total of 34 cm of water, compared with reported grower average exceeding 48 cm. Higher yields of 102 and 108 Mg/ha were observed in the 125% and 150% ETc treatments, respectively. Regarding crop quality, however, the 150% ETc treatment suffered greater incidence of pith breakdown and basal rot than the 100% treatment. Yields from the 50% and 75% treatments were below regional average. Aboveground biomass was evaluated 87 DAT. Fresh and dry biomass accumulations were positively related to applied water volume. Additional findings will be presented for a cauliflower trial conducted spring/summer 2019.

Johnson, Lee F.↗

Wireless Monitoring of the Height of Condensed Water in Steam Pipes

A wireless health monitoring system has been developed for determining the height of water condensation in the steam pipes and the data acquisition is done remotely using a wireless network system. The developed system is designed to operate in the harsh environment encountered at manholes and the pipe high temperature of over 200 °C. The test method is an ultrasonic pulse-echo and the hardware includes a pulser, receiver and wireless modem for communication. Data acquisition and signal processing software were developed to determine the water height using adaptive signal processing and data communication that can be controlled while the hardware is installed in a manhole. A statistical decision-making tool is being developed based on the field test data to determine the height of in the condensed water under high noise conditions and other environmental factors.

High Temperatures↗