SEARCH · Engineering Papers

Results for “FARMS”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 127 records · Page 7

All sources NASA NTRS DOE OSTI

NASA NTRS2020

Farm-Level Risk Factors of Increased Abortion and Mortality in Domestic Ruminants during the 2010 Rift Valley Fever Outbreak in Central South Africa

Background:Rift Valley fever (RVF) outbreaks in domestic ruminants have severe socio-economic impacts. Climate-based continental predictions providing early warnings to regions at risk for RVF outbreaks are not of a high enough resolution for ruminant owners to assess their individual risk. (2) Methods: We analyzed risk factors for RVF occurrence and severity at the farm level using the number of domestic ruminant deaths and abortions reported by farmers in central South Africa during the 2010 RVF outbreaks using a Bayesian multinomial hurdle framework. (3) Results: We found strong support that the proportion of days with precipitation, the number of water sources, and the proportion of goats in the herd were positively associated with increased severity of RVF (the numbers of deaths and abortions). We did not find an association between any risk factors and whether RVF was reported on farms. (4) Conclusions: At the farm level we identified risk factors of RVF severity; however, there was little support for risk factors of RVF occurrence. The identification of farm-level risk factors for Rift Valley fever virus (RVFV) occurrence would support and potentially improve current prediction methods and would provide animal owners with critical information needed in order to assess their herd’s risk of RVFV infection.

Melinda K Rostel↗

DOE OSTI2024

Solar Farm’s Microclimates Effects: Predicting Abundance and Visiting Frequency of Pollinators

The solar farm is garnering attention for its contribution to ecosystem services, particularly in supporting pollinators. Although numerous studies have focused on the distinct microclimates of solar farms, there has been limited effort to validate and model the impact of these conditions on insects [1]. To effectively evaluate and leverage the ecosystem services from solar farms in policymaking, understanding how insects react to microclimate variations in diverse designs and management methods is essential. This study aims to validate and model the impact of temperature and shade at solar farms on pollinator populations and their frequency of pollination as well as compare the potential for increased pollination under different types of panels within a solar grazing setup.

Chung, Hyun Yong↗

DOE OSTI2024

Evaluating Liquid Waste Transfers and their Impacts to the SRS Tank Farm to Support Operations and Closure

The Liquid Waste (LW) contractor at the Savannah River Site, Savannah River Mission Completion (SRMC), supports the storage, processing, and safe disposition of legacy, radioactive liquid waste. The LW Tank Farms contain approximately 127 million liters (33.5 million gallons) of liquid waste within 43 active, underground waste tanks. To meet mission critical milestones for the closure of waste tanks and processing of 34 million liters (9 million gallons) of salt waste per year by the LW Salt Waste Processing Facility (SWPF), an increase in Tank Farm operations, including waste tank transfers, is required. Waste is compiled in salt and sludge batches in the Tank Farms and transferred to SWPF and the Defense Waste Processing Facility (DWPF) for treatment. All waste tank transfers, such as waste removal and batch compilation transfers, must be pre-evaluated to ensure Documented Safety Analysis (DSA) requirements are met via Evaluated Transfer Approval Forms (ETAFs). Facility conditions and configurations may change as a result of a waste transfer. These changes must be reflected in the Tank Farms Emergency Response Datasheet (ERD), which contains data utilized for operation and emergency situations.

Peterson, Shelby R.↗

DOE OSTI2025

Large eddy simulation of wind farm performance in horizontally and vertically staggered layouts

This numerical investigation employs Large Eddy Simulation (LES) coupled with Actuator Disk Model (ADM) to evaluate wind farm layout optimization strategies. The study presents a systematic analysis of aligned, horizontal staggering, vertical staggering, and mixed (combination of horizontal and vertical) staggering configurations, aiming to establish optimal design parameters for enhanced power production. The investigation examines key performance metrics including mean velocity distributions, turbulence intensity characteristics, and power generation efficiency. Results demonstrate better performance of both horizontal and vertical staggering patterns compared to conventional aligned configurations, with horizontal staggering exhibiting notably higher power output than vertical arrangements. Our findings also suggest that mixed configurations, incorporating both horizontal and vertical staggering, can offer optimal performance characteristics. As a result, this research advances the understanding of wake interactions in complex wind farm layouts and provides design guidelines for maximizing wind farm power generation efficiency through strategic turbine positioning.

17 WIND ENERGY↗

DOE OSTI2026

Control co-design under uncertainty for offshore wind farms: Optimizing grid integration, energy storage, and market participation

Offshore wind farms (OWFs) are set to significantly contribute to global decarbonization efforts. Developers often use a sequential approach to optimize design variables and market participation for grid-integrated offshore wind farms. However, this method can lead to sub-optimal system performance, and uncertainties associated with renewable resources are often overlooked in decision-making. Here, this paper proposes a control co-design approach, optimizing design and control decisions for integrating OWFs into the power grid while considering energy market and primary frequency market participation. Additionally, we introduce optimal sizing solutions for energy storage systems deployed onshore to enhance revenue for OWF developers over time. This framework addresses uncertainties related to wind resources and energy prices. We analyze five U.S. west-coast offshore wind farm locations and potential interconnection points, as identified by the Bureau of Ocean Energy Management (BOEM). Results show that optimized control co-design solutions can increase market revenue by 3.2% and provide flexibility in managing wind resource uncertainties.

Control Co-design↗

DOE OSTI2024

User Impressions and Gait Analysis of Exoskeleton Device Usage in Generalized Tank Farm Activities

Tank farm workers involved in nuclear cleanup activities perform physically demanding tasks, typically while wearing heavy personal protective equipment (PPE). Exoskeleton devices have the potential to bring considerable benefit to this industry but have not been thoroughly studied in the context of nuclear cleanup. In this paper, we examine the performance of exoskeletons during a series of tasks emulating jobs performed on tank farms while participants wore PPE commonly deployed by tank farm workers. The goal of this study was to evaluate the effects of commercially available lower-body exoskeletons on a user’s gait kinematics and user perceptions. Three participants each tested three lower-body exoskeletons in a 70-min protocol consisting of level treadmill walking, incline treadmill walking, weighted treadmill walking, a weight lifting session, and a hand tool dexterity task. Results were compared to a no exoskeleton baseline condition and evaluated as individual case studies. The three participants showed a wide spectrum of user preferences and adaptations toward the devices. Individual case studies revealed that some users quickly adapted to select devices for certain tasks while others remained hesitant to use the devices. Temporal effects on gait change and perception were also observed for select participants in device usage over the course of the device session. Here, device benefit varied between tasks, but no conclusive aggregate trends were observed across devices for all tasks. Evidence suggests that device benefits observed for specific tasks may have been overshadowed by the wide array of tasks used in the protocol.

Tank farm↗

DOE OSTI2024

Floating Wind Farm Layout Optimization Considering Moorings and Seabed Variations

This paper presents a method for optimizing the layout of floating wind farms that accounts for realistic seabed variations and the consequent adjustments to the mooring systems required for different turbine positions. The mooring lines of floating wind farms create large spatial constraints that are depth-dependent, since mooring designs must adapt to variations in seabed conditions over the array area. We develop a layout optimization methodology that addresses this, adjusting mooring system designs based on the local seabed characteristics as the layout changes and using steady-state models for the wake effects and mooring lines. The approach includes design algorithms that adjust the anchor positions and line length to achieve the desired mooring line profile for different water depths, and a layout optimization framework that implements spatial constraints between the turbines, mooring lines, and lease area boundaries. Demonstrating the method on several cases shows the effect of the seabed and spatial-constraint factors, as well as their interactions, on the optimal array layout. This demonstration paves the way for scaling up the method, using more powerful optimization algorithms to handle larger farm sizes and situations with more intensely varied seabed conditions.

17 WIND ENERGY↗

DOE OSTI2026

Integrating agrivoltaics into smallholder farming systems to enhance food production and irrigation efficiency under climate stress

Smallholder agricultural growers and entrepreneurs (SAGE) have a crucial role in sustaining food security; their cultivation accounts for roughly 30% of global crop production and contributes substantially to the diversity and nutritional value of food systems. Despite their awareness of and flexibility to adapt to productivity challenges, SAGE communities remain highly vulnerable to heat and drought stress, which threatens both livelihoods and local food availability. While intensification and adaptive farm practices offer partial resilience, their capacity to buffer sudden climatic extremes remains limited. Agrivoltaics, the dual use of land for solar electricity generation and crop cultivation, has emerged as a promising strategy to enhance agricultural productivity and its resilience to climate extremes by altering microclimatic conditions. Although proven effective in hot and arid regions, the benefits of agrivoltaics for temperate climates and small-scale farms remain minimally explored. To address this gap, we evaluated the performance of a small-scale agrivoltaics system in a temperate climate for high-value crops, including leafy vegetables and garlic. We investigate whether the system can (i) protect crops during extreme heat events and (ii) enhance productivity and reduce irrigation requirements during hot and dry periods unsuitable for conventional production. Our findings provide evidence that agrivoltaics is a climate-resilient farming strategy under current and projected climate scenarios, capable of improving yields (by +43% to +127% for the leafy vegetables grown) and reducing water consumption, while creating complementary economic opportunities through decentralized energy generation systems. This work supports the integration of agrivoltaics into small-scale agricultural systems as an innovative pathway to strengthen food security, bolster farmer livelihoods, and enable multiple co-benefits from broader solar energy adoption.

14 SOLAR ENERGY↗

DOE OSTI2021

Cyber-physical security framework for Photovoltaic Farms

With the evolution of PV converters, a growing number of vulnerabilities in PV farms are exposing to cyber threats. To mitigate the influence of cyber-attack on PV farms, it is necessary to study attacks' impact and propose detection methods. To meet this requirement, a cyber-physical security framework is proposed for PV farms. Data integrity attacks (DIAs) are studied on different control loops. As μPMU is gaining in popularity, a lower sampling rate of μPMU data is applied to develop a detection algorithm. We have evaluated two data-driven methods, which are support vector machine (SVM) and long short-term memory (LSTM). Lastly, the data-driven methods verify the feasibility of μPMU data in attack detection.

Attack Impact Analysis↗

DOE OSTI2021

Hardware-in-the-Loop Testbed for Cyber-Physical Security of Photovoltaic Farms

In the last decades, modem grids with distributed energy resources, such as photovoltaic (PV) farms, are increasingly vulnerable to cyber-attacks that seriously affect the stability and performance of the power system. While cyber-physical security of smart grids is extensively studied, most of the existing work focuses on the grid level and neglects the modeling and features of device-level power electronics converters (PECs). Furthermore, establishing a high-fidelity simulation testbed that can simulate harmonic frequencies of the PV farm is in urgent need. In this paper, a high-fidelity and real-time hardware-in- the-loop testbed is built to simulate the harmonics of power electronics converters for cyber-physical security of PEC-enabled PV farms. Based on this testbed, the impact of typical cyber-attacks and physical faults on the PV converter can be analyzed, thus providing a foundation for cyber-attack detection, root cause diagnosis, and resilient control to mitigate the adverse effects of cyber-attacks.

14 SOLAR ENERGY↗

DOE OSTI2025

Sea surface warming and ocean-to-atmosphere feedback driven by large-scale offshore wind farms under seasonally stratified conditions

Offshore wind farms may induce changes in the upper ocean and near-surface atmosphere through coupled ocean-atmosphere feedbacks. Yet, the role of air-sea interactions mediated by offshore wind farms remains poorly understood. Using fully coupled ocean-atmosphere-wave model simulations for seasonally stratified conditions along the US East Coast, we show that simulated cumulative reductions in wind stress due to large-scale wind farm clusters lead to sea surface warming of 0.3° to 0.4°C and a shallower mixed layer. This warming drives upward heat fluxes, destabilizing the atmospheric boundary layer and enhancing wind stress, which partially offsets wake-induced wind deficits. These wake-ocean interactions influence near-surface meteorology and air-sea fluxes, suggesting that a coupled modeling approach may be necessary for assessing potential oceanographic impacts of offshore wind developments. However, ocean coupling exerts limited influence on winds at turbine-relevant heights or within downstream wakes, resulting in minimal impact on long-term energy. These findings suggest that models without ocean coupling may be adequate for wind energy applications.

17 WIND ENERGY↗

DOE OSTI2026

The Interactions Between Shading and Organic Fertilizer Application on Dry-farmed Tomato Grown Between Photovoltaic Panels

Agrivoltaic systems are mixed systems of solar photovoltaic (PV) panels and agricultural production, where shade from the panels can result in lower evapotranspiration for crops, which is of particular interest for dryland agriculture. Dry-farmed tomato (Solanum lycopersicum) production in the Willamette Valley of Oregon has lower total yields and higher rates of blossom-end rot (BER) than irrigated tomato production, resulting in reduced marketable yields. To determine how dry-farmed ‘Early Girl’ tomato performed in an agrivoltaics system, a trial was conducted at the Valley Creek Solar Project (Salem, OR, USA) in 2020, using three different amendment treatments and three levels of shading from the panels. Amendment treatments were 0N (receiving no fertilizer), 84N (receiving 84 kg·ha −1 N), and 168N (receiving 168 kg·ha −1 N), applied as processed chicken manure. Plants were estimated to receive an irradiance factor of 30%, 76%, and 89% for full-shade, partial-shade, and full-sun treatments respectively. There was an interaction between amendment treatments and shading treatments in their effects on unblemished yield (yield of fruit without BER or sunscald). The optimum fertilizer application for full-shade and partial-shade rows was 84N, the optimum for full-sun rows was 0N. Fertilizing these rows at these rates resulted in an unblemished yield for the aisle of 11.1 t·ha −1 , which was lower than unblemished yields reported in previous experiments and trials in open fields. However, these results are from a single location and a single year, and other solar sites may behave more similar to open-field conditions. Shading from the panels increased average fruit weight and decreased incidence of BER and sunscald, suggesting that crops were less drought stressed. This resulted in similar unblemished yields for the full-shade and full-sun plots at 84N and 168N. Applying fertilizer resulted in higher total yields, smaller average fruit weight, increased BER incidence, and decreased sunscald incidence. The results suggest a possible synergy between dry-farmed tomato production and agrivoltaics, although several concerns remain, including difficulties managing the vegetation under panels, rules restricting PVs on high-value agricultural soils, and the possibility of soil compaction during PV installation.

14 SOLAR ENERGY↗

DOE OSTI2021

Deep Reinforcement Learning for Automatic Generation Control of Wind Farms

This paper provides a model-free framework for real-time control of wind farms to accurately track a power reference signal. This problem requires tractable dynamical models for capturing the aerodynamic interaction between wind turbines and controllers that can make decisions in realtime given varying atmospheric conditions. In this paper, we propose a deep reinforcement learning framework to provide real-time yaw control of a wind farm. Modifications have been made to FLOw Redirection and Induction in Steady State (FLORIS), a modeling tool that incorporates transient wake behavior. The control problem is formulated to track a synthetic power reference signal based on historical atmospheric (wind speed and direction) information, price signals, and regulation deployment data from U.S. regional transmission operators. Results indicate that a wind farm, with this control paradigm, can achieve good tracking performance when tested with real atmospheric data.

49 EE - Wind and Water Power Program - Wind (EE-4W↗

DOE OSTI2026

A North Sea in Situ Evaluation of the Fitch Wind Farm Parameterization Within the Mellor-Yamada-Nakanishi-Niino and 3D Planetary Boundary Layer Schemes

Wind resource assessments and wind power forecasts that account for wind farm wakes are sensitive to the choice of planetary boundary layer (PBL) scheme. This work compares the one-dimensional Mellor-Yamada-Nakanishi-Niino (MYNN) PBL scheme with a three-dimensional PBL (3DPBL) scheme, evaluating predictions made with both schemes against two sets of North Sea in situ observations of wind farm wakes. The optimal PBL scheme varies based on the observations (FINO1 tower vs. aircraft), the quantity of interest (wind speed vs. turbulence kinetic energy [TKE]), and the error metric (bias, centered root mean square error [cRMSE], R2, and earth mover's distance [EMD]). Whereas 3DPBL wind speeds outperform MYNN wind speeds with respect to the cRMSE at the FINO1 site located at a single point within the turbine rotor layer, 3DPBL TKE bias is larger than MYNN TKE bias when compared to aircraft observations taken 100 m above a wind farm. Wind speeds in the aircraft region are ambiguous with regard to which PBL scheme is optimal. Aircraft MYNN wind speeds outperform 3DPBL wind speeds with respect to R2 and cRMSE but underperform with respect to bias and EMD. Future evaluations across broader temporal and spatial scales may offer further insight into model differences.

17 WIND ENERGY↗

DOE OSTI2022

Mooring System Cost Estimates for Wave Energy Farms in Shared Mooring Arrays

As wave energy converters (WECs) become more advanced and cost-efficient, so too must their mooring systems. A key question in the development plans for WECs is the cost of the mooring system, particularly for large wave farms. WEC devices deployed in a WEC farm array, where each device can be connected by shared mooring lines in various array layouts, have potential to reduce mooring system costs significantly. This paper presents the modeling and designing of mooring systems for large WEC arrays and the calculation of the cost of each mooring system to determine the change in cost as the number of WECs in a farm increases. A baseline mooring system for a single floating oscillating water column (OWC) WEC was developed for this analysis. The mooring system utilizes four anchored mooring lines connected to a square assembly of wire rope mooring lines, supported by four floating buoys, and attached to the floating WEC by four polyester rope mooring lines. This assembly, referred to as a floating cell, can be tiled to form various rectangular WEC arrays. The objective of this analysis is to determine how the mooring system cost changes as more WECs are added to an array layout, each with their own interconnected floating cell. To do this, complete mooring systems need to be designed for each WEC array layout. To narrow down the design space of a WEC array mooring system, a couple assumptions were made. It was assumed that the floating cell parameters of the baseline design were to stay constant across all floating cells in the WEC array. It was also assumed that the anchored mooring lines would be of the baseline configuration, a predominantly chain mooring line with a short section of polyester rope near the fairlead, and a drag-embedment anchor. These anchored lines were assumed to extend from the outer edges of the WEC array, inline with the headings of the wire rope mooring lines of the floating cells, or diagonal if extending from a corner of the WEC array. Full mooring systems were designed for 2xN and NxN WEC array layouts and efficiently simulated in the mooring dynamics simulation tool, MoorDyn, to ensure all dynamic constraints were met. The system costs were calculated and then refined by shortening unnecessary chain line lengths and reducing the chain diameters of the downstream anchored mooring lines. It was found that, in general, mooring system costs per WEC decrease when WECs are installed in an array. Compared to the baseline mooring system for a single WEC, the 2x3 mooring system array had the lowest mooring system cost per WEC, reducing the cost per WEC by 59%. The 3x3 and 4x4 array mooring systems also saw significant reductions in cost per WEC but had negligible cost savings between the two designs, primarily because the larger 4x4 mooring system requires larger chain diameters, which increases cost. These results provide an interesting glimpse into modeling, designing, and calculating the cost of mooring systems for large WEC arrays.

cost↗

DOE OSTI2024

Measuring and modeling soil moisture and runoff at solar farms using a disconnected impervious surface approach

Abstract Ground‐mounted photovoltaic sites are often treated as impervious surfaces in stormwater permits. This ignores the pervious soils beneath and between solar arrays and leads to an overestimation of runoff. Our objective was to improve solar farm stormwater hydrology models by explicitly considering the disconnected impervious nature of solar design and site characteristics. Experimental sites established on utility scale solar farms in Colorado, Georgia, Minnesota, New York, and Oregon had perennial vegetative plantings with mean precipitation ranging from 40.6 to 124.5 cm, and soil texture ranging from loamy sand to clay. Soil moisture measurements were collected beneath arrays, under drip edges, and in the vegetated area between arrays at each site. Hydrus‐3D models for soil moisture and stormwater hydrology were developed that accounted for precipitation falling on solar panels, drip edge redistribution of rainfall, infiltration, and runoff in the pervious areas between solar arrays and beneath panels. Drip edge runoff averaged 3‐ to 10‐times incident precipitation at the New York and Minnesota sites, respectively. Root mean square error values between measured sub‐hourly soil moisture and predicted moisture for large measured single storm events averaged 0.029 across all five sites. Predicted runoff depths were strongly affected by precipitation depth, soil texture, soil profile depth, and soil bulk density. Runoff depths across the five experimental sites averaged 13%, 25%, and 45% of the 2‐, 10‐, and 100‐year design storm depths, clearly showing that these solar farms do not behave like impervious surfaces, but rather as disconnected impervious surfaces with substantial infiltration of runoff in the vegetated areas between and beneath solar arrays.

Agriculture↗

DOE OSTI2021

Wind power production from very large offshore wind farms

In this work, we provide the first quantitative assessment of power production and wake generation from offshore wind energy lease areas along the U.S. east coast. Deploying 15-MW wind turbines, with spacing equal to the European average, yields electricity production of 116 TWh/year or 3% of current national supply. However, power production is reduced by one-third due to wakes caused by upwind wind turbines and wind farms. Under some flow conditions whole wind-farm wakes can extend up to 90 km downwind of the largest lease areas, and the frequency-weighted average area with a 5% velocity deficit is 2.6 times the footprint of the lease areas. Simulations including maritime corridors demonstrate reduction in the wake effects leading to power-efficiency gains and may offer contingent benefits. First-order scaling rules are developed that describe how “wake shadows” from large offshore wind farms scale with prevailing meteorology and wind turbine installed densities.

15 MW↗

DOE OSTI2025

Evolution of the ATLAS TDAQ online software framework towards Phase-II upgrade: Use of Kubernetes as an orchestrator of the ATLAS Event Filter computing farm

The ATLAS experiment at the LHC at CERN continuously evolves its TDAQ system to meet the challenges of new physics goals and technological advancements. As ATLAS prepares for the Phase-II Run 4 of the LHC, significant enhancements in the TDAQ Controls and Configuration (TDAQ-CC) tools have been designed to ensure efficient data collection, processing, and management. This abstract presents the evolution of ATLAS TDAQ-CC system leading up to Phase-II Run 4. As part of the evolution towards Phase-II, Kubernetes has been chosen to orchestrate the Event Filter (EF) farm. By leveraging Kubernetes, ATLAS can dynamically allocate computing resources, scale processing capacity in response to changing data taking conditions and ensure high availability of data processing services. The integration of the Kubernetes with the TDAQ Run Control framework enables perfect synchronisation between the experiment’s data acquisition components and the computing infrastructure. We will discuss the architectural considerations and implementation challenges involved in Kubernetes integration with the ATLAS TDAQ-CC system. We will highlight the benefits of using Kubernetes as an EF farm orchestrator, including improved resource utilization, enhanced fault tolerance, and simplified deployment and management of data processing workflows. In addition, we will report on the extensive testing of Kubernetes that was conducted using a farm of 2500 servers within the experiment data taking environment, demonstrating its scalability and robustness in handling the demands of the ATLAS TDAQ system for Phase-II. The adoption of Kubernetes represents a significant step forward in the evolution of ATLAS TDAQ-CC system, aligning with industry best practices in container orchestration.

Corso Radu, Alina [Univ. of California, Irvine, CA↗