Multi-Energy X-ray Radiography Source using Novel RF Technology
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Due to changes in electric distribution grid operation, new operation regimes have been recommended. Distribution grid optimal power flow (DOPF) has received tremendous attention in the research community, yet it has not been fully adopted across the utility industry. Our paper recognizes this problem and suggests a development and integration procedure for DOPF. We propose development of DOPF as a three step procedure of 1) processing the grid, 2) obtaining a tractable solution, and 3) implementing multiple solution algorithms and benchmarking them to improve application reliability. For the integration of DOPF, we demonstrate how a DOPF federate may be developed that can be integrated in a co-simulation environment to mimic the real-world conditions and hence improve its practicality to be deployed in the field. To demonstrate the efficacy of the proposed methods, tests on IEEE 123 bus system are performed where the usage of tractable formulation in DOPF algorithm development and its comparison to the benchmark solution are demonstrated.
DOE's PV Lifetime project was initiated in 2016 with the goal of accurately characterizing the early-life evolution of photovoltaic (PV) field performance. Different PV cell and module technologies result in different initial degradation rates due to effects like light-induced degradation (LID) and light and elevated temperature-induced degradation (LeTID). To accurately characterize the initial field degradation of maximum power (Pmp) requires the use of high-accuracy indoor IV curve measurements at standard test conditions. Therefore, PV modules involved in this study are removed from the field once or twice per year and brought indoors for measurement under constant temperature and irradiance conditions. Overall annual degradation rates are as follows: our first modules to be deployed (Jinko, Trina, QCells) have annual median degradation rate between -0.4%/yr and -0.5%/yr mainly concentrated in the first year. Mission Solar, LG and Panasonic modules are all displaying modest degradation, better than -0.3% / year. Indeed, Mission Solar fielded modules degraded less than their control modules which remain indoors and un-exposed. This is also true for the LONGi monofacial modules, which had some field degradation, but not as much as the degradation of the indoor control modules. The LONGi bifacial modules on the other hand have degraded more in the field than their monofacial counterparts, although still a modest amount (-0.4 %/yr). Of the four newest module types in the study, only one has had better than average degradation. REC360NP2 (N-type TOPCon) had a slight performance increase over the first year and a half of field deployment. For the other three new module types (plus one older module type), degradation was more rapid. In our study of 16 module types, four have demonstrated degradation faster than -1%/yr: two N-type Heterojunction, one PERC bifacial and one PERC shingled module. The two heterojunction modules in our study are degrading the most rapidly. Sunpreme n-HIT bifacial modules are showing a loss rate around -1.5%/yr, for over -10% total to date. This is largely attributed to loss in front-side Isc. This is distinct from the REC 405AA-Pure modules which have degraded -6.8% in only a year and a half, for an annualized decline of -3.9 %/yr. For this module type, the decline is roughly half in Voc, with the remaining split between FF and Isc. Of the remaining two module types, Prism Solar PERC bifacial has declined -5% total since 2019, although this loss appears to have stabilized in the most recent measurement. The Solaria PowerX-400R Shingled module type has also lost around -3.2% in the first 1.5 years of field deployment. It remains to be seen if these losses will continue with time.
Bifacial modules are increasingly deployed in the field and are expected to represent half of the market share within 10 years. Their rear structure differs from monofacial modules to allow additional light absorption. However, it brings new reliability challenges to address. In particular, the risk of potential-induced degradation (PID) is increased as both module sides are impacted. Different PID processes have been identified in the literature: shunting type (PID-s), polarization type (PID-p), Na penetration type, and corrosion type (PID-c). Their occurrence depends on the photovoltaic system configuration as well as the module's materials. Apart from PID-s, PID processes are not well understood and extensive research is needed to elucidate the PID scenario and underlying mechanisms. Herein, current knowledge about PID processes and their impact on the main bifacial modules in the market are gathered with the aim to guide future research. Bifacial module technologies and leakage current paths leading to PID are described. Indoor and outdoor PID testing methods are detailed. For each bifacial module technology, the PID processes are investigated with their indicators, mechanism and recovery process. Furthermore, PID-impacting factors and limitation solutions are finally reported and a state of the art on PID modeling is presented.
The use of lure-and-kill, large-volume ovitraps to control Aedes aegypti and Aedes albopictus populations has shown promise across multiple designs that target gravid females (adulticidal) or larvae post-oviposition (larvicidal). Here we report on a pilot trial to deploy 10 L yeast-baited ovitraps at select sites in Curepe, Trinidad, West Indies during July to December, 2019. Oviposition rates among ovitraps placed in three Treatment sites were compared to a limited number of traps placed in three Control areas (no Aedes management performed), and three Vector areas (subjected to standard Ministry of Health, Insect Vector Control efforts). Our goal was to gain baseline information on efforts to saturate the Treatment sites with ovitraps within 20–25 m of each other and compare oviposition rates at these sites with background oviposition rates in Control and Vector Areas. Although yeast-baited ovitraps were highly attractive to gravid Aedes females, a primary limitation encountered within the Treatment sites was the inability to gain access to residential compounds for trap placement, primarily due to residents being absent during the day. This severely limited our intent to saturate these areas with ovitraps, indicating that future studies must include plans to account for these inaccessible zones during trap placement.
The Delphire Sentinel is a modular fire detection and communications system operating as a mobile field unit, with low voltage DC power supplied by onboard photovoltaics (PV) and batteries. The Sentinel addresses several aspects of fire detection, communications and data analysis. The Sentinel's mobility enables it to be rapidly deployed and operate independently of existing power and communications networks. The duration of independent operation depends critically on the energy consumption of the systems and performance of the onboard PV and battery. The purpose of this testing is to ascertain the power draw and energy consumption of the Delphire Sentinel prototype system under several operational states, including various data transfer packet sizes, transmission time and frequencies, and communication pathways (Wi-Fi, cellular, satellite) expected to be encountered in field deployments. It will also include procedures to test the ability of the Sentinel to operate for extended periods without loss of functionality. Based on results from energy and power measurements, and anticipated duty cycles in field deployments, we will model annual system autonomy (e.g. loss of load probability) for off-grid operation in representative locations.
Weather radars with dual-polarization capabilities enable the study of various characteristics of hydrometeors, including their size, shape, and orientation. Radar polarimetric measurements, coupled with Doppler information, allow for analysis in the spectral domain. This analysis can be leveraged to reveal valuable insight into the microphysics and kinematics of hydrometeors in precipitation systems. This paper uses spectral polarimetry to investigate precipitation microphysics and kinematics in storm environments observed during the Remote Sensing of Electrification, Lightning, and Mesoscale/Microscale Processes with Adaptive Ground Observations (RELAMPAGO) field experiment in Argentina. This study uses range–height indicator scan measurements from a C-band polarimetric Doppler weather radar deployed during the field campaign. Here, in this work, the impact of storm dynamics on hydrometeors is studied, including the size sorting of hydrometeors due to vertical wind shear. In addition, particle microphysical processes because of aggregation and growth of ice crystals in anvil clouds, as well as graupel formation resulting from the riming of ice crystals and dendrites, are also analyzed here. The presence of different particle size distributions because of the mixing of hydrometeors in a sheared environment and resulting size sorting has been reported using spectral differential reflectivity (sZ dr ) slope. Spectral reflectivity sZ h and sZ dr have also been used to understand the signature of ice crystal aggregation in an anvil cloud. The regions of pristine ice crystals are identified from vertical profiles of spectral polarimetric variables in anvil cloud because of sZ h < 0 dB and sZ dr values around 2 dB. It is also found that the growth process of these ice crystals causes a skewed bimodal sZ h spectrum due to the presence of both pristine ice crystals and dry snow. Next, graupel formation due to riming has been studied, and it is found that the riming process produces sZ h values of about 10 dB and corresponding sZ dr values of 1 dB. This positive sZ dr indicates the presence of needle/columnar secondary ice particles formed by ice multiplication processes in the riming zones. Last, the temporal evolution of a storm is investigated by analyzing changes in hydrometeor types with time and their influence on the spectral polarimetric variables.
Crops with deeper roots would have multiple benefits, including better drought tolerance, reduced requirement for nitrogen fertilizer, and better sequestration of atmospheric CO 2 . DEEPER is an integrated platform of phenomic, genomic, and in silico technologies to generate maize lines with deeper roots. DEEPER is: LEADER (Leaf Elemental Accumulation from Deep Roots) is a breakthrough technology to nondestructively measure rooting depth by using the plant itself as a sensor. LEADER uses handheld X-ray Fluorescence spectrometry to quantify foliar accumulation of elements that are differentially distributed in the soil profile. LEADER is nondestructive and is orders of magnitude cheaper, faster, and more precise than any competing assay of rooting depth in the field. LEADER is able to distinguish deep-rooted from shallow-rooted maize lines in the field without the need for costly and noisy soil coring. RootRobot/DIRT3D, to automatically phenotype root architecture in any field, combining RootRobot, a mechatronics platform to excavate, clean, section, and image mature root crowns, with DIRT3D, software to quantify architectural traits in 3D. Anatomics, a high-throughput platform to phenotype root anatomy, combining LAT 2.0, a technology for 3D imaging of root anatomy and composition, with RootScan3D, software to automatically extract 3D anatomical and cell wall composition metrics from LAT 2.0 output. Using this platform we discovered two novel root traits, parenchyma cell wall thickness and multiseriate cortical sclerenchyma, that improve rooting depth and drought tolerance in maize and wheat. OpenSimRoot/Deep, software to simulate root interaction with hard subsoils. Using this platform we discovered novel concepts regarding how to increase crop rooting depth by modulating how individual root axes respond to hard soil. DeepGenes, a toolkit of genes, parent lines, and genomic selection strategies to enable breeding hybrids with deeper roots. We discovered 3 novel root genes that increase rooting depth in maize and wheat. DEEPER discovered novel root phenotypes for deeper rooting, and delivered validated ideotypes for deeper-rooted maize; novel technologies to rapidly assess root depth, root architecture and anatomy in field-grown plants; novel software tools for root modeling and 3D image analysis of root architecture and anatomy; and validated genes and genomic selection models to deploy traits for deeper rooting in maize breeding. Each DEEPER technology is transformative in its own right, and exceeds existing technologies. They are mutually synergistic, deployable for field-grown plants, and are ready for application. The phenotyping and modeling technologies are readily applicable to many crops, and genetic leads in maize may have utility in other grasses. Taken as a whole they represent a transformative platform to develop deeper-rooted crops, with greater drought tolerance, reduced fertilizer requirement, and greater carbon sequestration.
This report introduces a novel deployable origami baffle designed for telescopes and optical systems, which reduces stray light while maintaining high compactness ratios and low weight. This design leverages the planar nature of the end caps on a cylindrical Kresling origami fold to incorporate mounting points, deployable options, and baffle vanes. The adaptable nature of origami (number of faces, origami geometrical ratios, scaling, etc.) allows the design to easily conform to system requirements, including field of view, deployed length, stowed/deployed stability points, and available volume. Geometric ratios that exhibit bistability in both the stowed and deployed states are discussed in detail, as this results in a rigid structure that maintains its desired configuration. Several designs were conceptualized, and multiple small-scale prototypes were constructed. Potential applications include camera lens hoods, lightweight astronomy telescopes, and deployable baffles for space telescopes and optical systems.
The Advanced Materials and Manufacturing Technologies (AMMT) program within the Department of Energy (DOE) Office of Nuclear Energy has developed its current recommendation for promoting the use of combined ion irradiation and neutron irradiation for the accelerated qualification of materials to be deployed in nuclear reactors. This plan is intended to provide a collaborative path forward that can be adopted by academia, national laboratories, and industry, and has been developed with input from the regulatory research arm of the U.S. Nuclear Regulatory Commission (NRC). To deploy new materials or materials manufactured with new technologies, such as additive manufacturing, materials must be evaluated for reactor-induced degradation from the combination of harsh temperatures, corrosive environments, and radiation fields. However, rapid deployment of materials necessitates accelerated testing methods rather than relying on years of neutron irradiation in a material test reactor. Ion irradiation has demonstrated success in reproducing material microstructure and select property evolution resulting from neutron irradiation with three to four orders of magnitude reduction in time and cost, making it an ideal candidate for accelerated irradiation testing. This presentation provides context governing both the scientific and regulatory aspects of the proposed goal. The discussion is aimed at a broad audience including researchers from industry, national laboratories, and academia. The recommended path forward is presented as a conceptual framework of specific steps. In brief, the strategy entails developing an integrated ion and neutron irradiation test plan for the material property of interest based on the fundamental tenet of the linkage of microstructure and properties in materials. Physics-based modeling interprets ion irradiation data and predicts neutron irradiation microstructure and properties with uncertainty bounds. The first round of testing is sufficient for an initial licensing application using a risk-informed approach, while a minimum required neutron irradiation test plan reduces cost and time requirements. A surveillance program with witness specimens in-reactor provides additional data over time to improve model predictions to higher damage levels and further reduce uncertainty bounds, which can be used for license extensions or longer lifetimes in new license applications.
The Project objectives of this work were focused on the need to develop, investigate, and validate for field and commercial deployment robust pipeline surface treatments to prevent / minimize hydrate and other flow assurance solids deposition in subsea oil flowlines. A robust pipeline treatment that can prevent hydrate and wax/asphaltene adhesion/deposition will be a major fundamental breakthrough in hydrate and flow assurance science and engineering, and to critical Deepwater field operations. The project addressed the current major outstanding issue of mitigating gas hydrate and other solids deposition in different pipeline conditions, a major outstanding issue that has not been solved to-date, despite previous attempts/studies. The major goal of this project was to develop and investigate for deployment robust pipeline coatings to mitigate gas hydrate deposition in Deepwater oil flowlines, which will be critical in offshore leak and spill prevention. As oil and gas production wells mature, the water content and oil composition can change and increase the risk of gas hydrate, wax, and asphaltene deposition and blockages in flowlines, with the cost of complete inhibition becoming prohibitive. The ability to mitigate flow assurance risks in maturing flowlines can extend the life of the field, significantly reduce operational costs from inhibitor injection and prevent potential safety hazards to personnel and equipment and can prevent potential environmental hazards leading to catastrophic hydrocarbon emissions. This research allows for a novel, cost-effective method of mitigating gas hydrate and other pipeline solids deposition/blockages in flowlines, extending the life of the field while being minimally disruptive to normal flowline operation. The omniphobic surface treatment developed in this work can significantly improve the economics of energy transport by providing flow assurance and limiting catastrophic blowouts.
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Abstract not provided.
GE Research and its partner Prolec GE have designed, built and deployed in the field the world’s first flexible power transformer. The flexible power transformer is a transmission class 3-phase autotransformer configurable in impedance and in voltage which allows it to serve as a universal spare for multiple units in a given fleet. However, the key innovation in this new concept is the online adjustable leakage impedance which allows the transformer to change its impedance without interrupting the transmission line operation. The flexible power transformer can be designed with up to three low voltage transmission class ratings and up to 12 impedance values changeable both online and offline. This report provides an overview of the design, manufacturing, testing, and commissioning of the 165kV, 60MVA prototype built including the results of the field performance validation tests. The prototype was specified in collaboration with Cooperative Energy, the utility host. It was designed and tested in the factory according to IEEE standard C57.12.00 and followed all protocols for transportation, installation, and commissioning of a power transformer. In addition to the prototype, a flexible protection system capable of automatically adjusting its settings upon the transformer impedance was also developed and deployed in the for testing and validation. On September 3, 2021 the prototype was energized in Cooperative Energy’s substation in Columbia, Mississippi to become the world’s first flexible power transformer in operation. Its performances and impact on the grid operation were demonstrated through different field tests. Results obtained confirm that the impedance of the flexible transformer can be varied under load through its full range, from 4.3% to 9.3%, without adverse impacts on the line operation, the protection system, the transformer stability and health condition. Results also proved that the flexible transformer is very effective in controlling power transfer through the line or load sharing between units operating in parallel. Indeed, it was proven that higher impedances decrease the thruput power of the transformer while lower impedances increase it. Up to 26MW was controllable on a line loading of 45MVA. It was also possible to demonstrate that the variation of the transformer impedance has no effect on the circulating current between units in parallel, except a minor transient during the impedance change. It was also proven that the flexible protection relay can update its protection settings automatically when the impedance change was detected. The prototype has operated continuously for more than 12 months now with a peak load exceeding 50MVA corresponding to >80% of its ONAN power rating. No alarm, trip or sign of failure has been reported by the utility. In addition to the development and deployment of the flexible transformer prototype, investigations were carried out on new nanodielectric fluids to replace the mineral oil used in power transformers with the goal of reducing their footprint and weight. The key parameters that were targeted for improvement included the breakdown voltage to reduce clearances between windings and tank hence the footprint; viscosity and thermal conductivity to increase the cooling efficiency and therefore to reduce the winding material. Several nanodielectric mixtures with mineral oil including with alumina (Al2O3), titania (TiO2) and Borum Nitrate (BN) with different surfactants have been analyzed and tested. Unfortunately, despite encouraging results no nanofluid candidate has been found viable to replace mineral oil. With the formulations tested, breakdown voltages are generally similar to mineral oil at lower particle contents and worse at higher particle contents. Viscosity appreciably increased at particles concertation over 2 wt% and thermal conductivity increased slightly at 5wt% and appears to be 10-15% higher at 10 wt% particle content. It is recommended to continue investigations to find solutions that can help increase the power density of future flexible power transformers. Flexible power transformers can significantly help the future power grid by providing more flexibility and resiliency. Indeed, by providing voltage and impedance flexibility, flexible power transformers reduce the need for multiple spares, hence inventory costs for utilities. With their online controllable impedance, they can provide support to the grid and help manage short-circuit currents, power flow, line congestion, and grid stability which will become more important with higher penetrations of intermittent renewable resources. During the field validation tests, it was demonstrated that up to 26MW was controllable on a line loading of 45MVA when the transformer impedance was varied from its minimum to its maximum range. Also, with the impedance range, the short-circuit currents could be reduced by up to 38% at the load side of the transformer. With its controllable impedance, flexible transformers can be used in future strategies of grid resilience to help better prepare the grid to face forecasted severe events including storms, heat waves and contingencies. The flexible power transformers can also find role in other applications including high voltage transmission cables such as offshore wind farms where solutions for energizing the cables and managing the reactive power are of critical importance. The designed flexible power transformer is now fully validated and ready for commercialization. Further analysis on the benefits of flexible power transformers for grid stability and short-circuit management including current limiting capability, reclosure and line restoration, control of inrush current, sizing of flexible AC components (FACTS) would help its rapid adoption by the industry.
The Aerosol and Cloud Experiment in the Eastern North Atlantic (ACE-ENA) investigated properties of aerosols and subtropical marine boundary layer (MBL) clouds. Low subtropical marine clouds can have a large effect on Earth's radiative budget, but they are poorly represented in global climate models. In order to understand their radiative effects, it is imperative to understand the composition and sources of the MBL cloud condensation nuclei (CCN). The campaign consisted of two intensive operation periods (IOPs) (June–July 2017 and January–February 2018) during which an instrumented G-1 aircraft was deployed from Lajes Field on Terceira Island in the Azores, Portugal. The G-1 conducted research flights in the vicinity of the Atmospheric Radiation Measurement (ARM) Eastern North Atlantic (ENA) atmospheric observatory on Graciosa Island. An Aerodyne high-resolution time-of-flight aerosol mass spectrometer (HR-ToF-AMS) and Ionicon proton-transfer-reaction mass spectrometer (PTR-MS) were deployed aboard the aircraft, characterizing chemistry of non-refractory aerosol and trace gases, respectively. The eastern North Atlantic region was found to be very clean, with an average non-refractory submicrometer aerosol mass loading of 0.6 µg m −3 in the summer and 0.1 µg m −3 in the winter, measured by the AMS. Average concentrations of the trace reactive gases methanol and acetone were 1–2 ppb; benzene, toluene and isoprene were even lower, <1 ppb. Mass fractions of sulfate, organics, ammonium and nitrate in the boundary layer were 69 %, 23 %, 7 % and 1 % and remained largely similar between seasons. The aerosol chemical composition was dominated by sulfate and highly processed organics. Particulate methanesulfonic acid (MSA), a well-known secondary biogenic marine species, was detected, with an average boundary layer concentration of 0.021 µg m −3 , along with its gas-phase precursor, dimethyl sulfide (DMS). MSA accounted for no more than 3 % of the submicron, non-refractory aerosol in the boundary layer. Examination of vertical profiles of aerosol and gas chemistry during ACE-ENA reveals an interplay of local marine emissions and long-range-transported aged aerosol. A case of transport of biomass burning emissions from North American fires has been identified using back-trajectory analysis. In the summer, the non-refractory portion of the background CCN budget was heavily influenced by aerosol associated with ocean productivity, in particular sulfate formed from DMS oxidation. Episodic transport from the continents, particularly of biomass burning aerosol, periodically increased CCN concentrations in the free troposphere. In the winter, with ocean productivity lower, CCN concentrations were overall much lower and dominated by remote transport. These results show that anthropogenic emissions perturb CCN concentrations in remote regions that are sensitive to changes in CCN number and illustrate that accurate predictions of both transport and regional aerosol formation from the oceans are critical to accurately modeling clouds in these regions.
As applications of Artificial Intelligence (AI) continue to expand, there are increasing opportunities to leverage applied AI methodologies with mobile transportation focused embedded systems. Current applications of AI in transportation focus on a variety of areas, including fuel efficiency, safety, security, and other broad fields of optimization or detection. To leverage these AI workflows and methodologies in the field, teams must utilize complex embedded systems capable of implementing these AI-enabled algorithms in real-time. In this paper, we will investigate how these algorithms can be integrated into existing technologies leveraging vehicle data - such as the Controller Area Network Transport Security Tracking and Reporting Unit (C-STAR). The C-STAR technology is an embedded platform with onboard computation capable of running next generation algorithms in vehicle systems AI, such as preventative maintenance, driver authentication, and transport security. As deployed in the field, the C-STAR has a limited AI functionality –this paper will directly discuss how a device like C-STAR can be utilized and the advantages of integrating these new technologies. We will open with relevant background information and transportation projects that leverage AI, focusing specifically on those around transport security such as vehicle identification, anomaly detection, and deterrence. We will then extend this into potential opportunities and scaling for AI methodologies using platforms like the C-STAR. Finally, we will speak directly to the challenges of deploying AI-powered workflows, such as computing power needs, bandwidth, hallucinations, and other regulatory considerations.
We report physical experiments are often expensive and time-consuming. Test engineers must certify the compatibility of aircraft and their weapon systems before they can be deployed in the field, but the testing required is time consuming, expensive, and resource limited. Adopting Bayesian adaptive designs is a promising way to borrow from the successes seen in the clinical trials domain. The use of predictive probability (PP) to stop testing early and make faster decisions is particularly appealing given the aforementioned constraints. Given the high-consequence nature of the tests performed in the national security space, a strong understanding of new methods is required before being deployed. Although PP has been thoroughly studied for binary data, there is less work with continuous data, where many reliability studies are interested in certifying the specification limits of components. A simulation study evaluating the robustness of this approach indicates early stopping based on PP is reasonably robust to minor assumption violations, especially when only a few interim analyses are conducted. The simulation study also compares PP to conditional power, showing its relative strengths and weaknesses. A post-hoc analysis exploring whether release requirements of a weapon system from an aircraft are within specification with desired reliability resulted in stopping the experiment early and saving 33% of the experimental runs.
Relativistic charged -particle beams that generate intense longitudinal fields in accelerating structures also inherently couple to transverse modes. The effects of this coupling may lead to beam breakup instability and thus must be countered to preserve beam quality in applications such as linear colliders. Beams with highly asymmetric transverse sizes (flat beams) have been shown to suppress the initial instability in slab -symmetric structures. However, as the coupling to transverse modes remains, this solution serves only to delay instability. In order to understand the hazards of transverse coupling in such a case, we describe here an experiment characterizing the transverse effects on a flat beam, traversing near a planar dielectric lined structure. Further, the measurements reveal the emergence of a previously unobserved skew-quadrupolelike interaction when the beam is canted transversely, which is not present when the flat beam travels parallel to the dielectric surface. We deploy a multipole field fitting algorithm to reconstruct the projected transverse wakefields from the data. We generate the effective kick vector map using a simple two -particle theoretical model, with particle -in -cell simulations used to provide further insight for realistic particle distributions.