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The AgMIP Coordinated Climate-Crop Modeling Project (C3MP): Methods and Protocols

Climate change is expected to alter a multitude of factors important to agricultural systems, including pests, diseases, weeds, extreme climate events, water resources, soil degradation, and socio-economic pressures. Changes to carbon dioxide concentration ([CO2]), temperature, and water (CTW) will be the primary drivers of change in crop growth and agricultural systems. Therefore, establishing the CTW-change sensitivity of crop yields is an urgent research need and warrants diverse methods of investigation. Crop models provide a biophysical, process-based tool to investigate crop responses across varying environmental conditions and farm management techniques, and have been applied in climate impact assessment by using a variety of methods (White et al., 2011, and references therein). However, there is a significant amount of divergence between various crop models' responses to CTW changes (Rotter et al., 2011). While the application of a site-based crop model is relatively simple, the coordination of such agricultural impact assessments on larger scales requires consistent and timely contributions from a large number of crop modelers, each time a new global climate model (GCM) scenario or downscaling technique is created. A coordinated, global effort to rapidly examine CTW sensitivity across multiple crops, crop models, and sites is needed to aid model development and enhance the assessment of climate impacts (Deser et al., 2012). To fulfill this need, the Coordinated Climate-Crop Modeling Project (C3MP) (Ruane et al., 2014) was initiated within the Agricultural Model Intercomparison and Improvement Project (AgMIP; Rosenzweig et al., 2013). The submitted results from C3MP Phase 1 (February 15, 2013-December 31, 2013) are currently being analyzed. This chapter serves to present and update the C3MP protocols, discuss the initial participation and general findings, comment on needed adjustments, and describe continued and future development. AgMIP aims to improve substantially the climate, crop, and economic simulation tools that are used to characterize the agricultural sector, to assess future world food security under changing climate conditions, and to enhance adaptation capacity both globally and regionally. To understand better and improve the modeled crop responses, AgMIP has conducted detailed crop model intercomparisons at closely observed field sites for wheat (Asseng et al., 2013), rice (Li et al., in review), maize (Bassu et al., 2014), and sugarcane (Singels et al., 2013). A coordinated modeling exercise was one of the original motivations for AgMIP, and C3MP provides rapid estimation of crop responses to CO2, water, and temperature (CTW) changes, adding dimension and insight into the crop model intercomparisons, while facilitating interactions within the global community of modelers. C3MP also contributes a fast-track, multi-model climate sensitivity assessment for the AgMIP climate and crop modeling teams on Research Track 2 (Fig. 1), which seeks to understand the impact of projected climatic changes on crop production and food security (Rosenzweig et al., 2013; Ruane et al., 2014).

agriculture↗

Plateau Phenomenon in Gradient Descent Training of RELU Networks: Explanation, Quantification, and Avoidance

The ability of neural networks to provide ‘best in class’ approximation across a wide range of applications is well-documented. Nevertheless, the powerful expressivity of neural networks comes to naught if one is unable to effectively train (choose) the parameters defining the network. In general, neural networks are trained by gradient descent type optimization methods,a stochastic variant thereof. In practice, such methods result in the loss function decreases rapidly at the beginning of training but then, after a relatively small number of steps, significantly slow down. The loss may even appear to stagnate over the period of a large number of epochs, only to then suddenly start to decrease fast again for no apparent reason. This so-called plateau phenomenon manifests itself in many learning tasks. The present work aims to identify and quantify the root causes of plateau phenomenon.analysis is carried out in the setting of univariate ReLU networks. No assumptions are made on the number of neurons relative to the number of training data, and our results hold for both the lazy and adaptive regimes. Here, the main findings are: plateaux correspond to periods during which activation patterns remain constant, where activation pattern refers to the number of data points that activate a given neuron; quantification of convergence of the gradient flow dynamics; and, characterization stationary points in terms solutions of local least squares regression lines over subsets of the training data. Based on these conclusions, we propose a new iterative training method, the Active Neuron Least Squares (ANLS), characterised by the explicit adjustment of the activation pattern at each step, which is designed to enable a quick exit from a plateau. Illustrative numerical examples are included throughout.

97 MATHEMATICS AND COMPUTING↗

Radiation Hardened Engineered Substrates for Time and Space Resolution

Low Gain Avalanche Diodes (LGADs) have become sensors of choice for fast timing of minimum ionizing particles. The current generation of these devices suffer from only moderate radiation hardness, low fill factor, and limited design options. Cactus Materials Inc. proposes to develop sensors with gain layer implants buried beneath the surface which will, with AC coupling developed by Brookhaven National Laboratory (BNL) and University of California Santa Cruz (UC Santa Cruz) solve these problems. Fermilab has a major role in the CMS timing upgrade using the current generation of LGADs and development of AC-coupled, buried layer LGADs will solve some of the central problems inherent in this technology. Annex B included a two-year work plan, deliverables, schedule and funding for the project’s SBIR Phase II award to develop and test prototype LGADs utilizing wafer bonding technology and epitaxial growth, that will allow for fabrication of radiation hard AC coupled devices with 100% fill factor and adjustable operating point.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Planetary Nebulae with Supporting IR Data

We present new HST/WFPC2 imagery for the planetary nebula (PN) NGC 6818. Observations were made in line filters F437N, F487N, F502N, and F656N plus continuum filter F547M. The primary goal was to develop a high spatial resolution (approx. 0.1 in.) map of the intrinsic line ratio [O III] 4363/5007 and thereby evaluate the electron temperature (T(sub e)) and the mean-square T(sub e) variation (t(sup 2) across the PN. In this process we developed an extinction map from the F487N (H(beta)) and F656N (H(alpha)) images by comparing the observed line ratios in each pixel to the theoretical ratio and computing a c(H(beta)) map which was used to correct the observed 4363/5007 ratios for reddening. We also adjust for the continuum contribution to the line filter data. We present color-coded pictures of the reddening (c(H(beta))) map, the [O III] T(sub e) map, as well as our determinations of t(sup 2). The T(sub e) map shows a decline from approx. 14000 K in the inner regions to approx. 11000 K at the outer edge. Such a radial T(sub e) gradient is expected for a high-excitation nebula with a prominent He(++) zone such as NGC 6818. A composite of images taken in 3 filters (F656N, red; F487N, blue; and F502N, [O III] 5007, green) shows a roughly spherical outer envelope as well as a brighter vase-shaped interior "bubble". There is a prominent orifice to the North and a smaller one to the South, along the major axis, possibly caused by a blow-out from a fast wind. This nebula has an appearance remarkably similar to that of the PN NGC 3918 previously imaged with HST by H. Bond. We note from the continuum images (F547M) two stars in the nebular field that are fainter than the prominent central star; these are roughly 2-4 sec. N and NE of the central star. Further study is needed to establish whether or not there may be a physical association of either star with the central star.

Harrington, J. Patrick↗

Integrating Intelligent Hydro-informatics into an effective Early Warning System for risk-informed urban flood management

The urban drainage system constantly facing flooding issues in coastal and urban areas. Robust and accurate urban flood management, particularly considering fast-moving compound floods, is crucial to minimize the impact of flood disasters in coastal cities. Till now, Ho Chi Minh City (HCMC) lacks an effective means of urban flood management because of flood risk communication among residents. Existing flood risk communication tools rely on post-disaster flood model outcomes and data. Therefore, this research proposes a real-time Early Urban Flooding Warning System (EUFWS) integrated with a user-friendly web and app interface. The backbone of this system consists of flood models developed using machine learning (ML) algorithms, combined with big data and Web-GIS visualization, with ML serving as the core for constructing the EUFWS. EUFWS offer several key advantages: they are available at all times, accessible from anywhere, and provide a real-time, multi-user working platform. Additionally, the system is flexible, allowing for the easy addition of components and services and scalable, adjusting to workload demands. EUFWS have been successfully deployed in Thu Duc City, Vietnam, as a case study and are operating effectively. EUFWS have been successfully deployed in Thu Duc City, Vietnam, as a case study and are operating effectively. Research results indicate that EUFWS supported decision-makers to be effectively risk informed and make intelligent decisions during urban flood emergencies. Finally, this underscores the significant potential of integrating ML and information technology to enhance the management of smart urban drainage systems in flood-prone cities worldwide.

54 ENVIRONMENTAL SCIENCES↗

Tools and Methods for Optimization of Nuclear Plant Outages

Refueling outages are one of the most challenging phases in a nuclear power plants (NPP) operating cycle. Refueling outages are extremely costly for a NPP due to the large amount of required resources and because of lost revenue due to plant being off the grid. Outage durations have steadily decreased across the industry over that last few decades primarily due to improved planning and coordination, but there are still many plants that struggle to meet the performance metrics accomplished by other utilities. Schedule resilience is one of the issues. NPP outages require scheduling thousands of activities in a duration of around 30 days on average. Outage staff begin working on the schedule more than a year ahead of the outage start and make every effort to build a robust schedule. Despite the robust and detailed planning, once the outage starts, numerous emergent issues typically appear along with schedule delays requiring continuous replanning and adjusting. When schedule disruption occurs during an outage, plant staff make urgent efforts to recover but often not able to maintain the planned outage duration. These outage delays can cost a utility several million dollars per day. Tools that could help outage schedulers create a more resilient schedule and allow them to optimally reschedule emergent work could significantly reduce outage delays. One key aspect of creating a resilient schedule is to have accurate estimates for activity duration. Another important outage scheduling capability is the ability to schedule emergent work with minimal disruption. The Optimization of Outage Activities project under the Risk-Informed Systems Analysis Pathway (RISA) sponsored by Department of Energy (DOE) Light Water Reactor Sustainability (LWRS) program focuses on developing tools and methods to support nuclear power plants with optimization of outage schedules. The goal of the outage optimization is the completion of all planned and emergent outage activities as fast as possible while maintaining highest level of safety. This report describes the initial development of tools to support outage management that leverage computational and machine learning methods developed in other RISA and LWRS projects.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Deep reinforcement learning assisted co-optimization of Volt-VAR grid service in distribution networks

With the increasing penetration of distributed energy resources in distribution networks, Volt-VAR control and optimization (VVC/VVO) have become very important to ensure an acceptable quality of service to all customers. System operators can rely on slow-responding utility devices, including capacitor banks and on-load tap changing transformers, along with fast-responding battery and photovoltaic (PV) inverters for the VVC/VVO implementation. Because of variations in response time of these two classes of devices, and different control actions (discrete versus continuous), coordinated and optimal scheduling and operation have become of utmost importance. Here, this paper develops a look-ahead deep reinforcement learning (DRL)-based multi-objective VVO technique to improve the voltage profile of active distribution networks, decrease network and inverter power loss, and save the operational cost of the grid. It proposes a deep deterministic policy gradient (DDPG)-based approach to schedule the optimal reactive and/or active power set-points of fast-responding inverters, and a deep Q-network (DQN)-based DRL agent to schedule the discrete decisions variables of slow-responding assets. The reactive power output of PV and battery smart inverters are scheduled at 30-minute intervals and the capacitors’ commitment status is scheduled with several hour intervals. The proposed framework is validated on the modified IEEE 34-bus and 123-bus test cases with embedded PV and PV-plus-storage. To validate the efficacy of the proposed VVO, it is compared with several scenarios, including the base case without VVO, localized droop control of DERs, DDPG-only, and twin delayed DDPG (TD3) agent-based DRL techniques. The results justify the superior performance of the proposed method to improve the voltage profile, reduce network power loss, and minimize the look-ahead grid operational cost while minimizing the undesirable power losses in inverters as a result of power factor adjustments.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Time-interval distributions in a digital gamma multi-channel analyzer at extreme input rates

Here, this study explores the relationship between experimentally observed inter-event time-interval distributions (TIDs) and measured dead times for pulses generated by a HPGe gamma detector and processed by a digital spectrometer. The system utilizes a fast and slow channel, pile-up rejector, trapezoid filtering, and flash analog-to-digital converter. The experimentally derived TIDs were compared with theory for validation. The results demonstrate that the theoretical model reliably describes measured TIDs up to 40% dead time. However, significant distortion effects become increasingly pronounced at higher input rates. It appears that the deviation between the measured and calculated time-interval distributions take the shape of higher-order convolutions of the TID, which represent the time difference between counts for more than two successive events. In this work, theoretical functions for the TID are expanded to reproduce measurements up to 90%. This refinement in the interpretation and treatment of the measured TIDs provides improved accuracy and precision in the prediction of the true event rate and measured dead time in the counter. Even though it reflects occasional count loss that is specific to the set-up, it is expected that a similar adjustment may be applicable to other detection systems as well.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Sulfur Pellets Responses to a Bare and Steel Reflected Pulse of the Oak Ridge National Laboratory Health Physics Research Reactor

The experiments analyzed in this report were conducted at the Health Physics Research Reactor (HPRR), also known as the $\textit{Fast Burst Reactor}$. The reactor was designed and built at Oak Ridge National Laboratory (ORNL) in 1961. The HPRR was an unmoderated, unshielded fast reactor that used highly enriched uranium and molybdenum alloy as fuel. The reactor was initially sent to the Nevada Test Site in 1962, where it was used to evaluate radiation doses received as a result of the Hiroshima and Nagasaki bombings during World War II. A few years later, the reactor was sent back to ORNL to be part of the Dosimetry Application Research (DOSAR) facility shown in Figure 1, which included a reactor building shown on the left (west) of the picture and a control and laboratory building in the upper right corner (northeast). The critical assembly was used for numerous technical studies, including systems calibration, dosimetry, radiobiology of plants and animals, testing of radiation alarms, as well as teaching and training in radiation dosimetry and nuclear engineering. Between 1963 and 1987, the HPRR was operated for thousands of hours, achieving criticality close to 10,000 times and motivating many publications. The HPRR was decommissioned in 1987. The goal of this effort was to use historical data from operation of the HPRR to create a criticality accident alarm system (CAAS) benchmark to be included in the $\textit{International Handbook of Evaluated Criticality Safety Benchmark Experiments}$ (ICSBEP Handbook). A thorough inspection was performed of all available documentation and information available. The most promising experiments that were selected for evaluation were those described in the 1987 ORNL report entitled $\textit{Health Physics Research Reactor Reference Dosimetry}$, ORNL-6240. The report includes reference dosimetry results of the shielded and unshielded configurations of the HPRR after burst operations. Because of changes to the reactor positioning and storage systems that were made in 1985, the previous dosimetry reports became obsolete, and the newly designed experiments were needed to create the HPRR’s adjusted dosimetry data. The various results reported in ORNL-6240 include reference doses and dose equivalents from different conventions at different distances and elevations as determined using the detected neutron fluence and conversion factors. The HPRR neutron fluence was obtained through different methods, including sulfur pellet analysis and threshold detector unit data. Information about the HPRR spectrum was also obtained through Bonner sphere measurements. This benchmark is focused on a part of the measured sulfur fluences reported in Appendix H of ORNL-6240. Standard commercial sulfur pellets were placed at different distances from the HPRR centerline during burst operation and were activated due to the 32 S(n,p) 32 P reaction. The resulting 32 P activity was then measured and the information about the corresponding sulfur fluence and/or neutron dose could be extracted. Many of those measurements have 7 been performed with the HPRR in its bare configuration or with different shields (combinations of Lucite, concrete, steel). All the necessary, precise information about material and/or dimensions of the different shields was not found, so it was decided to focus only on the unshielded and steel-shielded configurations to minimize the benchmark uncertainty. A total of 31 cases (24 unshielded and 7 shielded cases at different positions) of sulfur fluence were selected before evaluation to develop the benchmark.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Robust bidding strategy for aggregation of distributed prosumers in flexiramp market

Distributed prosumers (DPs) are the grid customers that own energy production/storage assets. Due to the flexibility and fast response of their assets, they can procure ancillary service products (ASP) in the wholesale market. An appealing ASP offered by California ISO in the real-time market (RTM) is flexiramp for which market participants do not submit direct offers, and the compensation is based on their energy opportunity costs. Here in this report, we propose a bidding strategy model for DP aggregator participation in the RTM considering energy and flexiramp. First, we develop a risk-averse optimization to determine the optimal energy and reserve product to trade in day-ahead market while considering proper amounts of flexiramp to trade in the RTM. In the RTM, to obtain optimal amounts of energy and flexiramp, the aggregator must submit hourly multi-level price-quantity energy bids for multiple RTM intervals with 15 min time-steps. On this basis, we propose a robust hourly economic bidding strategy model that determines the optimal energy bids in the RTM. We develop an adjustable robust counterpart of the model to address the RTM energy and flexiramp price uncertainties. The simulation results justify the efficacy of our proposed framework in gaining profits from the wholesale market.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Ultrafast formation of domain walls of a charge density wave in SmTe 3

We study ultrafast x-ray diffraction on the charge density wave (CDW) of SmTe 3 using an x-ray free-electron laser. The high momentum and time resolution afforded by the x-ray laser enabled capturing fine wave-vector and time-dependent features of the CDW that originate from fast (in time) and sharp (in real space) variations of the CDW lattice distortion, which we attribute to an inversion of the order parameter. These domain inversions occur near the surface and are caused by the short penetration depth of the near-infrared pump with the wavelength centered at 800 nm, resulting in CDW domain walls perpendicular to the sample surface. These domain walls break the CDW long-range order on the scale of the x-ray probe depth, controlled experimentally by the x-ray incidence angle and suppress the diffraction intensity of the CDW for times much longer than the ~1–ps recovery of the electronic gap observed in time and angle-resolved photoemission spectroscopy. We model the spatial and temporal dependences of the order parameter using a simple Ginzburg-Landau model with all the parameters obtained from the published literature. We find reasonable agreement between the calculated and the measured diffraction across the momentum, time, fluence, and incidence angle dependence without adjusting any parameters. In conclusion, we reconstruct the spatial and temporal dependences of the lattice order parameter and find that at long times, depending on the pump fluence, multiple domain walls remain at distances of a few nanometers from the surface.

36 MATERIALS SCIENCE↗

Gear Test Assembly - Experimental Testing and Analysis of Gears and Bearings - FY2023

The Gear Test Assembly (GTA) is an experimental test apparatus built and installed in the Mechanisms Engineering Test Loop (METL) at Argonne National Laboratory (ANL). The focus of GTA has been to test larger radial spur gears sets machined from Inconel 718 along with a variety of bearing components that are to be used in the fuel handling machines built for use in pool-type sodium fast reactors. The testing in GTA also informs the design and material choices for the full-scale Gripper Test Assembly (GrTA) being developed by Argonne. To date, the Inconel 718 gears used in all six GTA experimental campaigns have completed over 23.2 million revolutions under various loads equivalent to approximately 37,156 simulated fuel assembly maneuvers (removal from and reinsertion to core) using a conventional height of a core assembly. While the heat treated and untreated tapered roller bearings and cylindrical pin thrust bearings used in the first five experimental campaigns have experienced mechanical or material failure after completing a range of fuel assembly maneuvers ranging from as early as 575 operations in Campaign #5 to 9800 operations in Campaign #1, Campaign #6 was the most successful campaign, achieving 22,563 maneuvers and was concluded before any catastrophic failure occurred. In this report we will present the results from the most recent campaigns, #5 and #6. The longevity of Campaign #6 was likely aided by a variety of adjustments made to the materials and components used and to the experimental testing procedures employed. In terms of materials and components, new gearboxes were fabricated, as opposed to using the old gear boxes which had been impacted by the previous bearing failures, and ball bearings were replaced with tapered roller bearings. The adjustments to the experimental procedure focused on a lowering of the maximum torque applied to the gears and bearings and the increase of the duration of each simulated fuel assembly maneuver conducted. This report will present and discuss the changes made to the materials, components, and procedures and the subsequent results for Campaign #5 and Campaign #6.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Design of a Proportional-Control-Based Advanced Control Strategy for Independent Temperature and Humidity Control of a Pre-Cooled Desiccant Air Cooling System

In this study, the control of a desiccant-wheel-based evaporative cooling system with a double-layer dew-point cooler system is emphasized. There are two dew-point evaporative coolers in the system and the air taken inside is subjected to pre- and post-cooling processes. The dehumidification process of the air taken in is carried out by the desiccant wheel after the pre-cooling process. A proportional-based control strategy has been developed to adjust the temperature and relative humidity of the room quickly and robustly with different operation modes for actuators to bring comfort with less energy consumption. In addition, an automatic Stop/Run mode has been added to the control strategy to save extra energy. With the developed control strategy, enabling the actuators to switch between the operation modes, more energy savings are achieved compared to both traditional ON/OFF and proportional controls. The accuracy and applicability of the developed control strategy were analyzed and it was observed that the room comfort reached the desired levels successfully under all disruptive effects. The control inputs and the energies consumed by all the actuators were investigated and it was determined that 21.19% more energy savings are provided by adding the automatic Stop/Run feature. With the multi-mode control strategy, a total of 40.90% less energy consumption is achieved compared to the classical ON/OFF control technique. Thus, it is seen that the controller developed for the desiccant-wheel-based evaporative cooler is a viable method to provide fast and robust comfort conditions with less energy.

42 ENGINEERING↗

Dielectric and magnetic properties of microwave-absorbing FeAl x O y catalysts fabricated via solution combustion synthesis

Iron-based alumina (FeAl x O y ) nanocomposites are microwave-absorbers and catalysts, which makes them promising for emerging microwave-assisted thermocatalytic technologies. Solution combustion synthesis (SCS) has been used to synthesize FeAl x O y powders, and prior work has demonstrated that adjusting SCS parameters significantly changes phase composition and specific surface area of the products. However, it is unclear how synthesis parameters affect their microwave-absorbing properties, which are essential for optimizing microwave-assisted technologies. To address this challenge, in the present work, twelve different FeAl x O y products were synthesized at different combinations of the SCS parameters such as two fuels (citric acid and glycine), two heating modes (hotplate and muffle furnace), and three Fe:Al molar ratios (2:1, 1:1, 1:2). Dielectric and magnetic properties of the products were characterized using a network analyzer and a vibrating sample magnetometer. Based on the measured permittivity and permeability, penetration depth and reflection loss were calculated as a function of frequency and bed thickness. The products were heated by microwaves at 2.45 GHz and then examined with X-ray diffraction (XRD) analysis. For all products, the magnetic saturation was lower than for bulk iron oxides because of the small crystallite size and aluminum substitution. The use of glycine induced high dielectric losses and enabled fast microwave-heating rates compared to citric acid. Higher Fe:Al ratio also led to higher dielectric and magnetic losses. With glycine fuel, SCS in a furnace induced larger penetration depth and lower microwave absorption than SCS on a hotplate. The minimization of reflected power was more sensitive to the thickness of the product bed than to the frequency of the electromagnetic field. Post-heating XRD analysis revealed different phase transformations in the FeAl x O y powders depending on the SCS parameters. As a result, an FeAl x O y material, synthesized via incipient wetness impregnation, lacked magnetic losses and did not heat well as compared to the SCS products.

Combustion synthesis↗

Smart Manufacturing Pathways for Industrial Decarbonization and Thermal Process Intensification

Rapid decarbonization is fast becoming the primary environmental and sustainability initiative for many economic sectors. Industry consumes more than 30 % of all primary energy in the United States and accounts for nearly 25 % of all greenhouse gas (GHG) emissions. More than 70 % of energy consumed by the industrial sector is related to thermal processes, which are also the largest contributors of carbon emissions, overwhelmingly due to the combustion of fossil fuels. Thermal process intensification (TPI) seeks to dramatically improve the energy performance of thermal systems through technology pillars focusing on alternative energy sources and processes, supplemental technologies, and waste heat management. The impacts of TPI have significant overlap with the goals of industrial decarbonization (ID) that seeks to phase out all GHG emissions from industrial activities. Emerging supplemental technologies such as smart manufacturing (SM) and the industrial internet of things (IoT) enable significant opportunities for the optimization of manufacturing processes. Combining strategies for TPI and ID with SM and IoT can open and enhance existing opportunities for saving time and energy via approaches such as tighter control of temperature zones, better adjustment of thermal systems for variations in production levels and feedstock properties, and increased process throughput. Data collected by smart processes will also enable new advanced solutions such as digital twins and machine learning algorithms to further improve thermal system savings. Herein, this paper examines the individual pathways of TPI, ID, and SM and how the combination of all three can accelerate energy and GHG reductions.

42 ENGINEERING↗

A FFT Method for the Quasiclassical Selection of Initial Ro-Vibrational States of Triatomic Molecules

This paper describes the use of an exact fast Fourier transform (FFT) method to prepare specified vibrational-rotational states of triatomic molecules. The method determines the Fourier coefficients needed to describe the coordinates and momenta of a vibrating-rotating triatomic molecule. Once the Fourier coefficients of a particular state are determined, it is possible to easily generate as many random sets of initial cartesian coordinates and momenta as desired. All the members of each set will correspond to the particular vibrational-rotational state selected. For example, in the case of the ground vibrational state of a non-rotating water molecule, the calculated actions of 100 sets of initial conditions produced actions within 0.001 h(bar) of the specified quantization values and energies within 5 cm(sup -1) of the semiclassical eigenvalue. The numerical procedure is straightforward for states in which all the fundamental frequencies are independent. However for states for which the fundamental frequencies become commensurate (resonance states), there are additional complications. In these cases it is necessary to determine a new set of "fundamental" frequencies and to modify the quantization conditions. Once these adjustments are made, good results are obtained for resonance states. The major problems are in labelling the large number of Fourier coefficients and the presence of regions of chaotic motion. Results are presented for the vibrational states of H2O and HCN and the ro-vibrational states of H2O.

Eaker, Charles W.↗

Magnetogram Forecast: An All-Clear Space Weather Forecasting System

Solar flares and coronal mass ejections (CMEs) are the drivers of severe space weather. Forecasting the probability of their occurrence is critical in improving space weather forecasts. The National Oceanic and Atmospheric Administration (NOAA) currently uses the McIntosh active region category system, in which each active region on the disk is assigned to one of 60 categories, and uses the historical flare rates of that category to make an initial forecast that can then be adjusted by the NOAA forecaster. Flares and CMEs are caused by the sudden release of energy from the coronal magnetic field by magnetic reconnection. It is believed that the rate of flare and CME occurrence in an active region is correlated with the free energy of an active region. While the free energy cannot be measured directly with present observations, proxies of the free energy can instead be used to characterize the relative free energy of an active region. The Magnetogram Forecast (MAG4) (output is available at the Community Coordinated Modeling Center) was conceived and designed to be a databased, all-clear forecasting system to support the operational goals of NASA's Space Radiation Analysis Group. The MAG4 system automatically downloads nearreal- time line-of-sight Helioseismic and Magnetic Imager (HMI) magnetograms on the Solar Dynamics Observatory (SDO) satellite, identifies active regions on the solar disk, measures a free-energy proxy, and then applies forecasting curves to convert the free-energy proxy into predicted event rates for X-class flares, M- and X-class flares, CMEs, fast CMEs, and solar energetic particle events (SPEs). The forecast curves themselves are derived from a sample of 40,000 magnetograms from 1,300 active region samples, observed by the Solar and Heliospheric Observatory Michelson Doppler Imager. Figure 1 is an example of MAG4 visual output

Barghouty, Nasser↗

Science Enhancements by the MAVEN Participating Scientists

NASA implemented a Participating Scientist Program and released a solicitation for the Mars Atmosphere and Volatile EvolutioN mission (MAVEN) proposals on February 14, 2013. After a NASA peer review panel evaluated the proposals, NASA Headquarters selected nine on June 12, 2013. The program's intent is to enhance the science return from the mission by including new investigations that broaden and/or complement the baseline investigations, while still addressing key science goals. The selections cover a broad range of science investigations. Included are: a patching of a 3D exosphere model to an improved global ionosphere-thermosphere model to study the generation of the exosphere and calculate the escape rates; the addition of a focused study of upper atmosphere variability and waves; improvement of a multi-fluid magnetohydrodynamic model that will be adjusted according to MAVEN observations to enhance the understanding of the solar-wind plasma interaction; a global study of the state of the ionosphere; folding MAVEN measurements into the Mars International Reference Ionosphere under development; quantification of atmospheric loss by pick-up using ion cyclotron wave observations; the reconciliation of remote and in situ observations of the upper atmosphere; the application of precise orbit determination of the spacecraft to measure upper atmospheric density and in conjunction with other Mars missions improve the static gravity field model of Mars; and an integrated ion/neutral study of ionospheric flows and resultant heavy ion escape. Descriptions of each of these investigations are given showing how each adds to and fits seamlessly into MAVEN mission science design.

Thermosphere↗