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DOE OSTI2026

Extraction of the Collins-Soper Kernel from a Joint Analysis of Experimental and Lattice Data

We present a first joint extraction of the Collins-Soper kernel (CSK) combining experimental and lattice QCD data in the context of an analysis of transverse-momentum-dependent distributions (TMDs). Based on a neural-network parametrization, we perform a Bayesian reweighting of an existing fit of TMDs using lattice data, as well as a joint TMD fit to lattice and experimental data. We consistently find that the inclusion of lattice information shifts the central value of the CSK by approximately 10% and reduces its uncertainty by 40%–50%, highlighting the potential of lattice inputs to improve TMD extractions.

Avkhadiev, Artur [Massachusetts Inst. of Technolog↗

DOE OSTI2023

An Online Joint Optimization–Estimation Architecture for Distribution Networks

Here in this article, we propose an optimal joint optimization-estimation architecture for distribution networks, which jointly solves the optimal power flow (OPF) problem and static state estimation (SE) problem through an online gradient-based feedback algorithm. The main objective is to enable a fast and timely interaction between the OPF decisions and state estimators with limited sensor measurements. First, convergence and optimality of the proposed algorithm are analytically established. Then, the proposed gradient-based algorithm is modified by introducing statistical information of the inherent estimation and linearization errors for an improved and robust performance of the online OPF decisions. Overall, the proposed method eliminates the traditional separation of operation and monitoring, where optimization and estimation usually operate at distinct layers and different time scales. Hence, it enables a computationally affordable, efficient, and robust online operational framework for distribution networks under time-varying settings.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2022

Computation of Direct Sensitivities of Spatial Multibody Systems With Joint Friction

Abstract Friction exists in most mechanical systems and may have a major influence on the dynamic performance of the system. The incorporation of friction in dynamic systems has been a subject of active research for several years owing to its high nonlinearity and its dependence on several parameters. Consequently, optimization of dynamic systems with friction becomes a challenging task. Gradient-based optimization of dynamical systems is a prominent technique for optimal design and requires the computation of model sensitivities with respect to the design parameters. The novel contribution of this paper is the derivation of the analytical methodology for the computation of direct sensitivities for smooth multibody systems with joint friction using the Lagrangian index-1 formulation. System dynamics have been computed using two different friction models; the Brown and McPhee, and the Gonthier et al. model. The methodology proposed to obtain model sensitivities has also been validated using the complex finite difference method. A case study has been conducted on a spatial multibody system to observe the effect of friction on the dynamics and model sensitivities, compare sensitivities with respect to different parameters and demonstrate the numerical and validation aspects. Since design parameters can have very different magnitudes and units, the sensitivities have been scaled with the parameters for comparison. Finally, a discussion has been presented on the interpretation of the case study results. Due to the incorporation of joint friction, ‘jumps’ or discontinuities are observed in the model sensitivities akin to those observed for hybrid dynamical systems.

Engineering↗

DOE OSTI2024

UFNet: Joint U-Net and Fully Connected Neural Network to Bias Correct Precipitation Predictions from

Paper information. Shuang Yu, Indrasis Chakraborty, Gemma J. Anderson, Donald D. Lucas, Yannic Lops, and Daniel Galea. UFNet: Joint U-Net and fully connected neural network to bias correct precipitation predictions from climate models. Artificial Intelligence for the Earth Systems, 2024. Overview. This work develops the UFNet methodology to correct E3SM historical precipitation projection bias. The UFNet deep learning framework consists of a two-part architecture: a U-Net convolutional network to capture the spatiotemporal distribution of precipitation and a fully connected network to capture the distribution of higher-order statistics. The joint network, termed UFNet, can simultaneously improve the spatial structure of the modeled precipitation and capture the distribution of extreme precipitation values. Below we provide guidance for applying UFNet to correct the Energy Exascale Earth System Model (E3SM; Golaz et al. 2019) daily precipitation projection over the contiguous United States (CONUS). Getting started 1. Obtain the historical climate simulation and observation data. The E3SM historical simulation data are available through https://aims2.llnl.gov/search/cmip6/. The CPC unified gauge-based analysis of daily precipitation can be found through https://psl.noaa.gov/data/gridded/data.cpc.globalprecip.html. The ECMWF atmospheric reanalysis of the 20th century (ERA-20C) data are available through https://www.ecmwf.int/en/forecasts/datasets/reanalysis-datasets/era-20c. The spatial resolution of E3SM and observed datasets are both regridded to a common 1° resolution grid using conservative interpolation. The regridded E3SM, CPC and ERA-20C with 1° resolution can be found throught ./data/. 2. Train the fully connected network (DNN) Python train_dnn.py 3. Train the UFNet Python train_ufnet.py 4. Evaluation and compared with the baseline Python evaluation.py

Lucas, DonaldD↗

DOE OSTI2021

Joint Modeling of Access Mode and Parking Choice of Air Travelers Using Revealed Preference Data

Airport ground access mode choice is distinct from everyday mode choice decisions, necessitating context-specific choice model estimation. Understanding airport ground access mode choice decisions is not only important for developing infrastructure planning strategies, but also for assessing the impacts of emerging modes on airport revenues, particularly from parking. However, parking choice is an often-overlooked dimension in airport ground access choice modeling. This paper addresses this gap through the development of a joint model of airport access mode and parking option choice using a passenger survey conducted at Dallas-Fort Worth (DFW) International Airport in 2015. Compared with a traditional conditional logit model that does not consider parking options available at DFW airport, the joint model of mode and parking decisions was found to generate more realistic values of travel time and was shown to have better predictive performance, both of which are critical for obtaining better airport parking revenue estimates and identifying traveler cohorts who may respond more strongly to potential policies targeting curb congestion and parking demand.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2021

Model-Data for Joint Estimation of Biogeochemical Model Parameters from Multiple Experiments: A Bayesian Approach Applied to Mercury Methylation

This modeling archive supports the manuscript submitted for publication in the Environmental Modeling and Software. This study is supported by ORNL-SFA and IDEAS-Watershed. This study aims to improve calibration of complex biogeochemical models using datasets from multiple experiments targeting specific subprocesses. The proposed Bayesian joint-fitting scheme calibrates the entire biogeochemical model in one go using all the available datasets and estimate parameter uncertainties using Markov Chain Monte Carlo (MCMC). This allows for complete propagation of uncertainties and utilization of the information shared between different datasets. Mapping joint distribution of parameters guides model improvement by identifying null spaces in the parameter space. This archive contains files used to perform MCMC, post-process outputs and visualize results.

East Fork Poplar Creek↗

DOE OSTI2022

The Roles of Interface, Adherend, and Adhesive in Plasma- and Other-treated Joints of Metals and FRP Materials Under Shear Deformation

This work investigated the role of interface, adherend, and adhesive in adhesively-bonded metal-metal, metal-CFRTP, and CFRTP-CFRTP combinations with plasma-treated surfaces under shear deformation. To this end, aluminum alloys (AA5052 and AA6061) and short-carbon-fiber-reinforced polyamide 66 (CFRPA66) were used as examples and performed through single lap shear testing. The results showed that air plasma surface treatment can improve the shear behavior of adhesively-bonded AA5052-CFRPA66 and CFRPA66-CFRPA66 joints with about 20% enhanced lap shear strength compared to non-treated cases. Failure surface morphology of plasma-treated CFRPA66 adherend confirmed this improvement by showing an increased amount of adhesive failure than interfacial failure between CFRPA66 and adhesive. But this is not true for AA5052-AA6061 joints with plasma-treated surfaces exhibiting almost no enhanced lap shear strength. This study also showed the importance of selecting a proper surface modification method for the enhancement of adhesive-bonded structures under shear deformation through the analysis of the results in this study and in the literature. For fiber-reinforced polymers (FRPs), improving FRP/adhesive interface may be prioritized via different surface modification methods (e.g., plasma, chemical coating, etc.) than adhesive modification methods. However, for surface-cleaned metals, toughening adhesive via different enhancement methods (e.g., nano-particles, chemical enhancement, etc.) may be more important than improving metal/adhesive interface. These insightful results are valuable in the area of multi-materials joining.

Qiao, Yao↗

DOE OSTI2020

Joint optimal scheduling for electric vehicle battery swapping-charging system based on wind farms

Insufficiencies in charging facilities limit the broad application of electric vehicles (EVs). In addition, EV can hardly represent a green option if its electricity primarily depends on fossil energy. Considering these two problems, this paper studies a battery swapping-charging system based on wind farms (hereinafter referred to as W-BSCS). In a W-BSCS, the wind farms not only supply electricity to the power grid but also cooperate with a centralized charge station (CCS), which can centrally charge EV batteries and then distribute them to multiple battery swapping stations (BSSs). The operational framework of the W-BSCS is analyzed, and some preprocessing technologies are developed to reduce complexity in modeling. Then, a joint optimal scheduling model involving a wind power generation plan, battery swapping demand, battery charging and discharging, and a vehicle routing problem (VRP) is established. Then a heuristic method based on the exhaustive search and the Genetic Algorithm is employed to solve the formulated NP-hard problem. Numerical results verify the effectiveness of the joint optimal scheduling model, and they also show that the W-BSCS has great potential to promote EVs and wind power.

17 WIND ENERGY↗

DOE OSTI2020

AMS / BARC Joint Survey (Summary Report)

Report describes a series of joint aerial radiation survey flights at various locations in Southern Nevada and Colorado performed by AMS and BARC (U.S. and India). The flights were conducted over areas of well-characterized natural background in Nevada, at the Large-Area Calibration Pads at Grand Junction, CO, and over real ground contamination at the Nevada National Security Site. The intention of the joint surveys was to compare the responses, processes, and procedures of each country’s aerial radiation detection system. These systems can detect and map ground contamination that may result from a nuclear or radiological accident or incident, and play a significant role in the national radiological emergency response capabilities of both countries.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

DOE OSTI2021

A Comparative Study of Joint Modeling Methods and Analysis of Fasteners [Slides]

Motivation: Crucial aspect of mechanical design is joining methodology of parts. Ability to analyze joint and fasteners in system for structural integrity is fundamental. Different modeling representations of fasteners include spring, beam, and solid elements. Various methods compared for linear system to decide method appropriate for design study. New method for modeling fastener joint is explored from full system perspective. Analysis results match well with published experimental data for new method.

42 ENGINEERING↗

DOE OSTI2022

Atmospheric Cold Plasma Jet Coating and Surface Treatment for Improved Adhesive Bonding Performance of Dissimilar Material Joints Subject to Harsh Environmental Exposure

The program goal was the development and demonstration of a novel material coating system using an innovative atmospheric cold microwave plasma jet to enable surface functionalization for corrosion protection, wear resistance and improved bonding strength. The technical approach was directed towards proof-of-concept demonstration of advanced point-of-manufacturing material bonding to improve adhesive joint performance subject to harsh environmental exposure. The assembled team, consisting of the researchers at the University of Illinois, end-users at General Motors and small business manufacturer Starfire Industries, successfully demonstrated a single, cost-effective, high-volume production process that meets the requirements of multi-material combinations relevant to the energy-intensive transportation industry (e.g. Al-steel, Mg-steel, Al-Mg and Al-CFRP joints for body-in-white structures) while eliminating offline pretreatment for Al and Mg alloy substrates that are energy intensive, have chemical waste disposal issues, and add cost. Technical demonstration of dissimilar material joining while maintaining bonding strength and cohesion after long-duration environmental exposure was accomplished for all materials of interest. This novel approach has broad applicability for manufacturing in automotive, aerospace, marine, railcar, and specialty consumer goods, etc.

36 MATERIALS SCIENCE↗

DOE OSTI2025

HTS to NbTi Joints for Fusion Magnet Cost Savings

This paper describes methods of employing high field High Temperature Superconductors (HTS), only where high field capability and high current density is needed in superconducting coils. The approach lends itself, in particular, to Toroidal Field (TF) coils used in fusion reactors. The initial idea was to develop a conductor joint design or designs that would allow joints between expensive high field High Temperature Superconductors (HTS) Rare Earth Barium Copper Oxide (REBCO) conductors to low cost NbTi lower field conductors.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2026

Fundamentals of Solar PV Bolted Joint Loosening and Prevention

The photovoltaic (PV) industry has long reported anecdotal accounts of systems exhibiting intermittent or chronic fastener loosening, including joints that fail to maintain preload despite multiple re-tightening attempts. These occurrences are frequently, and often incorrectly, attributed to installer errors, vibration, or loading beyond design expectations (e.g., extreme weather events). Loose fasteners have serious implications and can significantly impact solar PV systems’ performance, reliability, and safety. However, effective bolted joint design and proper assembly practices can mitigate or eliminate loosening. Until the US Department of Energy’s Solar Energy Technologies Office (SETO) funded research on fasteners and solar PV structures, there was a notable gap in understanding the causes of loosening in solar PV systems.

14 SOLAR ENERGY↗

DOE OSTI2026

Joint modeling of water and energy for resilience and flexibility

This white paper addresses the intersection of energy and water resources for potable water, considering energy-for-water through joint systems modeling. Specifically, we focus on the opportunities to promote joint resilience in water and power systems through coupled modeling to inform decision-makers.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2026

Stochastic Modeling of the Joint Neutron Number-Cumulative Fission Fragment Kinetic Energy Deposition Distribution and its Statistical Moments [Slides]

We investigate the joint distribution of the neutron number and cumulative fission-fragment kinetic energy (FKE) deposition, with a specific focus on low-order statistical moments: the mean, variance, and correlation. Starting from a point-kinetic framework, we derive a forward Master equation (FME) for the joint distribution and develop the corresponding moment equations.

42 ENGINEERING↗

DOE OSTI2026

New directions for joint neutrino oscillation measurements with T2K and NOvA

The first joint analysis of data from the NOvA and T2K neutrino oscillations experiments was published in 2025, offering the most precise measurements of the larger mass splitting $\Delta m_{32}^{2}$, the largest mixing angle $\theta_{23}$, and the CP-violating phase $\delta_{CP}$ available at the time. In addition to working towards a reanalysis with additional data collected since that analysis, the collaborations are now exploring possible constraints on BSM physics scenarios. This poster will discuss the potential of a joint measurement of parameters in a framework treating effective non-standard neutral-current neutrino-matter interactions, NC-NSI. Uniquely, the differing baselines and energies of T2K and NOvA allow strong constraints to be set on the electron-muon and electron-tau parameters of NSI contributions to the Hamiltonian, while at the same time maintaining good sensitivity to the standard 3-flavor neutrino oscillations parameters, including the CP phase.

Mikola, Veera [Glasgow U.]↗

DOE OSTI2023

Microstructural, Corrosion, and Mechanical Characterization of Friction Stir Welded Al 6022-to-ZEK100 Mg Joints

Friction stir welded (FSW) aluminum–magnesium lightweight vehicle joints have gained significant interest due to their high strength-to-weight ratio. In this work, the corrosion resistance of this material is analyzed through electrochemical tests, which include open circuit potential (OCP) inspection and potentiodynamic polarization (PD) scanning. Weight loss measurements tested the corrosion rate of the FSW weld through cyclic corrosion testing (CCT) according to the standard SAEJ 2334. Mechanical properties were also investigated, including lap-shear strength, micro- and nano-hardness mapping, and true stress–strain curves as a function of local processing history. The electrochemical results indicate that the center weld zone’s corrosion property stays between the two base alloys. Indentation-based testing demonstrated that the weld zone behaves differently from base alloys. Lap shear strength surprisingly did not drop much even after eight weeks of cyclic corrosion tests, indicating that the joint did not allow any ingress of the electrolyte.

36 MATERIALS SCIENCE↗

DOE OSTI2020

In Situ and Post-Mortem Characterizations of Ultrasonic Spot Welded AZ31B and Coated Dual Phase 590 Steel Joints

Ultrasonic spot welding using different welding conditions was applied to join dissimilar metals of galvanized DP590 steel and AZ31B magnesium sheets. In situ high-speed imaging, digital image correlation, and infrared thermography were utilized to quantitatively study the interfacial relative motion, surface indentation, and heat generation across the joint faying interface and the sheet/sonotrode interfaces under the welding condition of moderate welding power and short welding time. For welds made with high power and long welding time, lap shear tensile tests as well as fatigue tests were carried out. Different fracture modes were observed after the lap shear tensile tests and fatigue tests performed under different peak loads. Post-weld cross-sectional analysis with scanning electron microscopy coupled with energy dispersive X-Ray spectroscopy revealed the variation of morphology and chemical composition at the joint interface for welds made with different welding conditions.

36 MATERIALS SCIENCE↗