Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “complex loading”

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.

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

At least 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

On the Use of Surfactant-Complexed Chitosan for Toughening 3D Printed Polymethacrylate Composites

This work reports a simple approach to prepare toughened 3D-printed polymethacrylate (PMA) composites using surfactant-modified chitosan (SMCS) particles at loadings between 2–10 wt%. Chitosan (CS) is modified with anionic surfactant, sodium dodecyl sulfate, via ionic complexation to facilitate compatibility and dispersion of CS to PMA matrix by non-covalent interactions between the components. The study successfully demonstrates high-accuracy 3D printing of composites with significant improvements in the overall mechanical properties. The composite with the best loading of 8 wt% SMCS shows a tensile modulus of 1.23 ± 0.05 GPa, a tensile strength at 49.8 ± 0.96 MPa, a yield stress at 33.3 ± 1.48 MPa, and a strain-at-ailure 10.3 ± 0.61%, which are 45%, 40%, 32%, and 68% higher than neat PMA, respectively. This provides a significant improvement in toughness at 4.92 ± 0.55 MJ m -3 for the composite, 184% higher than that of neat PMA. The marked increase in toughness is due to enhanced filler-matrix interactions which improve the ability of the 3D printed composite to absorb energy under tensile load. The results from this work provide new understandings into the strategies for design and preparation of stereolithography 3D printed materials reinforced with toughening fillers from renewable resources.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Load balancing for multi-beam additive manufacturing systems

As powder bed fusion (PBF) additive manufacturing (AM) becomes a more mature field, system configurations are gradually moving away from the classic single heat source, layer-by-layer system configurations towards unconventional system configurations that offer higher throughput. Higher throughput systems allow PBF systems to be considered for a larger variety of industrial applications. However, the inclusion of multiple heat sources, or beams, also increases the complexity of the control schemes needed. For multi-beam systems with overlapping fields of view, the distribution of workload, or load balancing, across these beams directly affects the total print time for a build. Additionally, the probability of any beam failing in a multi-beam system increases with the number of beams. While manual methods of load balancing and dealing with beam failures are reasonable for current generation multi-beam systems, as system configurations become more complex, manual methods will become prohibitively inefficient. Here, this paper introduces two different ways to load balance multi-beam systems of various configuration types, regardless of their complexity, which are highly performant. A consequence of this performance is the enablement of on-the-fly load balancing in the event a beam fails, thus improving system robustness.

36 MATERIALS SCIENCE↗
DOE OSTI2022

A review of active probing-based system identification techniques with applications in power systems

System identification is becoming a relevant research area for numerous applications in power grids due to the increasing complexity of the system. A paradigm shift in power system infrastructure driven by renewable energy resources, controllable loads, and new power electronics technologies have given rise to new challenges in power systems operation and control. This increased complexity of power systems and unavailability of physics-based models of most inverter-based resources requires that traditional modeling of power systems approaches be complemented by system identification-based black or grey box modeling techniques. In light of the importance of system identification and little attention paid to the applications of these techniques in transforming power systems, this paper provides a comprehensive review of active probing-based system identification methods in the context of power system applications. It reviews applications of both linear and nonlinear system identification with discussion on their potential and key takeaways. To motivate a further practical use in power systems, the paper provides an example of system identification, to develop a state space model of an unknown plant with step-by-step details. The paper highlights the advantages of using modern power electronics-based sources in the identification process and discusses the emerging research directions for future.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Structural integrity of additively manufactured stainless steel with cold sprayed barrier coating under combined cyclic loading

Integration of metal additive manufacturing (AM) and cold spray (CS) technologies provide an unprecedented opportunity to manufacture coated material systems with complex geometrical features. The application of these material systems in functionally critical components requires adequate structural integrity, particularly in the presence of cyclic loading. This article researches the multiaxial fatigue (axial-torsional cyclic loading) behavior of a coated material system consisting of 15Cr-5Ni precipitation-hardening stainless steel (15-5 PH SS) substrate additively manufactured by direct metal laser sintering with a layer of chromium carbide nickel (CrC-Ni) barrier coating deposited by CS. The influence of AM and CS-induced residual stresses on fatigue performance of test specimens was thoroughly studied. Additionally, the effect of surface roughness and processes induced defects were considered to explain the crack growth mechanism. Stresses assessed by synchrotron X-ray diffraction indicated a substantial accumulation of residual stresses, particularly in the outer surface of the as-fabricated 155 PH SS specimens. The state of residual stress was changed notably following the deposition of CrC-Ni coating in the axial, hoop, and radial directions of the fatigue test specimen. Also, CS deposition of CrC-Ni coating caused significant improvement in the surface quality of the additively manufactured components. Fatigue test results indicated, CS deposition of CrC-Ni substantially enhances the fatigue life of the AM-produced 15-5 PH SS substrate in all loading conditions, particularly in the high cycle fatigue regime. The improvement in the fatigue life of the specimens with coating was associated with a reduction in equivalent residual stress at the substrate surface and improvement in the specimens' surface condition (i.e., reduced surface roughness). The fractographic analysis of the specimen indicated the cracks tend to initiate in the surface of both as-fabricated and cold-sprayed specimens. However, the mechanism of crack growth changed notably following the deposition of CrC-Ni coating. The cracks tended to propagate in the planes parallel or with a small deviation from the build layers of the AM-produced specimens. On the other hand, deposition of CrC-Ni coating increased the deviation of crack growth plane from the build layers of the substrate.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Extrapolation of the Rainflow-Counted Load Ranges for Fatigue Assessment of the Wind Turbine's Blades

Wind turbine design standards recommend the use of statistical modeling coupled with extrapolation of the short-term load data to long-term periods for fatigue reliability assessment. However, statistical error and computational expense can limit the accuracy of such approaches. In the case of wind turbine blades, the errors are more significant because of the high material fatigue exponent that makes the damage estimations more sensitive to variations. In addition, due to different excitation sources, the flapwise load range histogram is not unimodal, and thus its statistical modeling is complex. In the present work, we provide three methods for statistical modeling of the flapwise bending moment ranges including a novel approach based on frequency-based separation of the modes. The first two methods are simplified approaches for modeling the most crucial load ranges using unimodal distributions and the third method involves multimodal distribution fitting. The research is based on 3600 10-minute aeroelastic simulations of DTU 10MW case study wind turbine from which a benchmark damage equivalent load (DEL) is calculated. The DEL calculated by each of the three proposed methods is compared to this reference. The results show that the conventional approach based on using 6 seeds as well as using mixture models fitted on the limited data lead to under-conservative results with errors up to 23%. On the other hand, the simplified unimodal approaches provided in this work can provide conservative estimations of the fatigue damage with mean values 5% and 12% higher than the benchmark. However, the variability of the DEL estimates is higher when using unimodal extrapolation of the load ranges, and the data can be conservative by 17.5%. The proposed unimodal fits suggested for modeling and extrapolation of the blade's load ranges provide less errors relatively and most importantly conservative DEL estimations while maintaining computational efficiency.

blade fatigue↗
DOE OSTI2021

Spread Spectrum Time Domain Reflectometry and Steepest Descent Inversion to Measure Complex Impedance

In this paper, we present a method for estimating complex impedances using reflectometry and a modified steepest descent inversion algorithm. We simulate spread spectrum time domain reflectometry (SSTDR), which can measure complex impedances on energized systems for an experimental setup with resistive and capacitive loads. A parametric function, which includes both a misfit function and stabilizer function, is created. The misfit function is a least squares estimate of how close the model data matches observed data. The stabilizer function prevents the steepest descent algorithm from becoming unstable and diverging. Steepest descent iteratively identifies the model parameters that minimize the parametric function. We validate the algorithm by correctly identifying the model parameters (capacitance and resistance) associated with simulated SSTDR data, with added 3 dB white Gaussian noise. With the stabilizer function, the steepest descent algorithm estimates of the model parameters are bounded within a specified range. Furthermore, the errors for capacitance (220pF to 820pF) and resistance (50 Ω to 270 Ω) are < 10%, corresponding to a complex impedance magnitude |R +1/jωC| of 53 Ω to 510 Ω.

14 SOLAR ENERGY↗
DOE OSTI2023

A Six-Phase Space Vector PWM Technique for Wide Bandgap Device-Based Three-Level Inverters

This article presents a space vector pulsewidth modulation (SVPWM) technique for wide bandgap (WBG) device-based three-level (3L) six-phase inverters. Implementation of the SVPWM techniques for any six-phase inverter is complex for its high number of possible voltage vectors. Different six-phase load configurations are also possible depending on the angle between two consecutive phases and neutral point connections. The implementation techniques change depending on the load configuration. Moreover, a common neutral point for all six phases leads to circulating currents. Capacitor voltage balancing is also needed for 3L inverters. Capacitor voltage balancing and addressing the circulating current problem further increases the implementation complexity. In this article, a generalized SVPWM technique is proposed for the six-phase 3L inverters that is implementable using two three-phase 3L SVPWM blocks. The SVPWM technique also ensures dc bus capacitor voltage balancing and minimizes circulating current. Here, the SVPWM technique is experimentally verified using a GaN-based 3L six-phase active neutral point clamped (ANPC) inverter prototype, and the results are presented in this article.

42 ENGINEERING↗
DOE OSTI2020

Distribution System Segmented Model Simplification with Independent Dynamically Changing End-Use Loads

With more emerging technologies in power distribution systems, to support quasi-static time-series (QSTS) simulation over short time frames, accurately modeling the dynamic behavior of end-use load under various conditions is im- portant. However, time and cost can be a burden for the QSTS simulation of thousands of houses representing dynamic load behaviors on large distribution feeders. There are two main contributions of this paper in order to reduce the QSTS simulation complexity. First, the paper presents a method to stochasti- cally model the dynamic behavior of end-use load for QSTS simulations. Second, using the stochastically modeled load behavior as an input to a distribution sys- tem, and building on our previous QSTS simulation simplification/acceleration method that relies on uniform load behavior, this paper presents a segment substitution approach for the simplification of distribution system models with independent dynamically changing end-use loads. Our numerical results show that compared to GridLAB-D, a software tool that simulates end-use load be- havior through physical models, the proposed stochastic modeling approach achieved an 89.3% simulation time reduction for end-use loads, while accurately capturing the temporally changing total load behavior. Moreover, the QSTS simulation of a large test distribution system through OpenDSS showed that the proposed simplification method decreased the feeder simulation time by a factor of three at less than 0.3% voltage error. Compared to our previous method with independent dynamic loads, the voltage error is reduced by a factor of four.

Power distribution system modeling, stochastic pro↗
DOE OSTI2020

COM1 , a factor of alternative non‐homologous end joining, lagging behind the classic non‐homologous end joining pathway in rice somatic cells

SUMMARY The role of rice ( Oryza sativa ) COM1 in meiotic homologous recombination (HR) is well understood, but its part in somatic double‐stranded break (DSB) repair remains unclear. Here, we show that for rice plants COM1 conferred tolerance against DNA damage caused by the chemicals bleomycin and mitomycin C, while the COM1 mutation did not compromise HR efficiencies and HR factor (RAD51 and RAD51 paralogues) localization to irradiation‐induced DSBs. Similar retarded growth at the post‐germination stage was observed in the com1‐2 mre11 double mutant and the mre11 single mutant, while combined mutations in COM1 with the HR pathway gene ( RAD51C ) or classic non‐homologous end joining (NHEJ) pathway genes ( KU70 , KU80 , and LIG4 ) caused more phenotypic defects. In response to γ‐irradiation, COM1 was loaded normally onto DSBs in the ku70 mutant, but could not be properly loaded in the MRE11 RNAi plant and in the wortmannin‐treated wild‐type plant. Under non‐irradiated conditions, more DSB sites were occupied by factors (MRE11, COM1, and LIG4) than RAD51 paralogues (RAD51B, RAD51C, and XRCC3) in the nucleus of wild‐type; protein loading of COM1 and XRCC3 was increased in the ku70 mutant. Therefore, quite differently to its role for HR in meiocytes, rice COM1 specifically acts in an alternative NHEJ pathway in somatic cells, based on the Mre11–Rad50–Nbs1 (MRN) complex and facilitated by PI3K‐like kinases. NHEJ factors, not HR factors, preferentially load onto endogenous DSBs, with KU70 restricting DSB localization of COM1 and XRCC3 in plant somatic cells.

Xu, Zhan↗
DOE OSTI2020

NOPCHAP1 is a PAQosome cofactor that helps loading NOP58 on RUVBL1/2 during box C/D snoRNP biogenesis

Abstract The PAQosome is a large complex composed of the HSP90/R2TP chaperone and a prefoldin-like module. It promotes the biogenesis of cellular machineries but it is unclear how it discriminates closely related client proteins. Among the main PAQosome clients are C/D snoRNPs and in particular their core protein NOP58. Using NOP58 mutants and proteomic experiments, we identify different assembly intermediates and show that C12ORF45, which we rename NOPCHAP1, acts as a bridge between NOP58 and PAQosome. NOPCHAP1 makes direct physical interactions with the CC-NOP domain of NOP58 and domain II of RUVBL1/2 AAA+ ATPases. Interestingly, NOPCHAP1 interaction with RUVBL1/2 is disrupted upon ATP binding. Moreover, while it robustly binds both yeast and human NOP58, it makes little interactions with NOP56 and PRPF31, two other closely related CC-NOP proteins. Expression of NOP58, but not NOP56 or PRPF31, is decreased in NOPCHAP1 KO cells. We propose that NOPCHAP1 is a client-loading PAQosome cofactor that selects NOP58 to promote box C/D snoRNP assembly.

Abel, Yoann↗
DOE OSTI2022

A low-cost centralized HVAC control system solution for energy savings, load shedding, and improved maintenance

University campuses rely on centralized controls for managing and optimizing complex HVAC systems in larger buildings. However, most campuses also have many smaller buildings with packaged HVAC systems controlled by a stand-alone thermostat. Even when these distributed and often overlooked systems have modern programmable thermostats, they cannot be centrally monitored or controlled, and they are typically not programmed adequately. This paper describes the implementation of a low-cost centralized control solution for these systems serving smaller campus buildings, mostly under 5,000 sf and representative of light commercial spaces. Thanks to advances in technology spurred by residential and commercial IoT developments, simple networked thermostat solutions exist that can easily replace original thermostats, and, connect these systems to a web-based portal for monitoring and control. We show that, with small customizations, these platforms can be integrated into facility management workflows. Beyond the energy savings potential from improved scheduling and closer management of these systems, there are significant advantages for maintenance crews since these systems can now be monitored on smart phones or tablets. A grid-responsive load-shedding program has also been implemented for additional cost savings. The networked thermostats can also be connected to additional systems such as economizer controls for improved ventilation management and energy savings. With data from these systems integrated centrally, it can also be used for improved analytics and fault detection. A toolkit has been developed to share the program with other campuses, whether for energy savings, improved management of ventilation, or a more proactive maintenance approach.

Fauchier-Magnan, Nicolas↗
DOE OSTI2023

Sensitivity analysis of numerical modeling input parameters on floating offshore wind turbine loads

Abstract. Floating wind turbines must withstand a unique and challenging set of loads from the wind and ocean environment. To de-risk development, accurate predictions of these loads are necessary. Uncertainty in modeling predictions leads to larger required safety factors, increasing project costs and the levelized cost of energy. Complex aero-hydro-elastic modeling tools use many input parameters to represent the wind, waves, current, aerodynamic loads, hydrodynamic loads, and structural properties. It is helpful to understand which of these parameters ultimately drives a design. In this work, an ultimate and fatigue-proxy load sensitivity analysis was performed with 35 different input parameters, using an elementary effects approach to identify the most influential parameters for a case study involving the National Renewable Energy Laboratory (NREL) 5 MW baseline wind turbine atop the OC4-DeepCwind semisubmersible during normal operation. The importance of each parameter was evaluated using 14 response quantities of interest across three operational wind speed conditions. The study concludes that turbulent wind velocity standard deviation is the parameter with the strongest sensitivity; this value is important not just for turbine loads, but also for the global system response. The system center of mass in the wind direction is found to have the highest impact on the system rotation and tower loads. The current velocity is found to be the most dominating parameter for the system global motion and consequently the mooring loads. All tested wind turbulence parameters in addition to the standard deviation are also found to be influential. Wave characteristics are influential for some fatigue-proxy loading but do not significantly impact the extreme ultimate loads in these operational load cases. The required number of random seeds for stochastic environmental conditions is considered to ensure that the sensitivities are due to the input parameters and not due to the seed. The required number of analysis points in the parameter space is identified so that the conclusions represent a global sensitivity. The results are specific to the platform, turbine, and choice of parameter ranges, but the demonstrated approach can be applied widely to guide focus in parameter uncertainty.

17 WIND ENERGY↗
DOE OSTI2020

Revisiting the first Sandia Fracture Challenge with transient deformation heating and strain localization considerations

In this study, we present a systematic experimental study and accompanying theoretical analysis of the dependence of ductile fracture on strain localization, strain hardening rates, deformation-induced thermal softening, and transient heat conduction under spatially uniform as well as spatially heterogeneous deformation. Spatially uniform cases are studied via standard dogbone shaped specimens subject to uniaxial tension. Spatially heterogeneous deformation is studied via the so-called Sandia Fracture Challenge (SFC) specimen, which is a standard compact tension specimen modified with three machined holes in front of a blunt notch. We utilize the same precipitation hardened martensitic stainless steel used in the first SFC experiments, i.e. 15-5 PH with an H1075 heat treatment. We also study 15-5 PH in Condition A and with the H900 heat treatment, each of which has a different hardening behavior and ductility. We find that the ductility does not correlate with the deformation to first crack initiation in the SFC specimen. Instead, hardening rates are better correlated. Moreover, a re-examination finds that an accurate calibration of the hardening rates is strongly correlated with accurate blind predictions of ductile fracture in the SFC specimens. Given that thermal softening can greatly affect hardening rates, we provided a thermographic analysis of deformation-induced heating and transient heat transfer in both the dogbone shaped samples and the SFC specimens. Transient heating in stainless steels is found to have first-order effects on the strain at the onset of necking, strain to fracture, as well as strain localization and ductile fracture in complex geometries even under so-called quasi-static loading rates.

42 ENGINEERING↗
DOE OSTI2021

GFCCLib: Scalable and efficient coupled-cluster Green's function library for accurately tackling many-body electronic structure problems

Coupled-cluster Green’s function (GFCC) calculation has drawn much attention in the recent years for targeting the molecular and material electronic structure problems from a many-body perspective in a systematically improvable way. However, GFCC calculations on scientific computing clusters usually suffer from expensive higher di- mensional tensor contractions in the complex space, expensive inter-process communi- cation, and severe load imbalance, which limits it’s routine use for tackling electronic structure problems. Here we present a numerical library prototype that is specifically designed for large-scale GFCC calculations. The design of the library is focused on a systematically optimal computing strategy to improve its scalability and efficiency. The performance of the library is demonstrated by the relevant profiling analysis of running GFCC calculations on remote giant computing clusters. The capability of the library is highlighted by computing a wide near valence band of a fullerene C60 molecule for the first time at the GFCCSD level that shows excellent agreement with the experimental spectrum.

Peng, Bo↗
DOE OSTI2021

Toward Guided Mutagenesis: Gaussian Process Regression Predicts MHC Class II Antigen Mutant Binding

Antigen-specific immunotherapies (ASI) require successful loading and presentation of antigen peptides into the major histocompatibility complex (MHC) binding cleft. One route of ASI design is to mutate native antigens for either stronger or weaker binding interaction to MHC. Exploring all possible mutations is costly both experimentally and computationally. To reduce experimental and computational expense, here we investigate the minimal amount of prior data required to accurately predict the relative binding affinity of point mutations for peptide-MHC class II (pMHCII) binding. Using data from different residue subsets, we interpolate pMHCII mutant binding affinities by Gaussian process (GP) regression of residue volume and hydrophobicity. We apply GP regression to an experimental data set from the Immune Epitope Database, and theoretical data sets from NetMHCIIpan and Free Energy Perturbation calculations. We find that GP regression can predict binding affinities of nine neutral residues from a six-residue subset with an average R 2 coefficient of determination value of 0.62 ± 0.04 (±95% CI), average error of 0.09 ± 0.01 kcal/mol (±95% CI), and with an receiver operating characteristic (ROC) AUC value of 0.92 for binary classification of enhanced or diminished binding affinity. Similarly, metrics increase to an R2 value of 0.69 ± 0.04, average error of 0.07 ± 0.01 kcal/mol, and an ROC AUC value of 0.94 for predicting seven neutral residues from an eight-residue subset. Our work finds that prediction is most accurate for neutral residues at anchor residue sites without register shift. This work holds relevance to predicting pMHCII binding and accelerating ASI design.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Comparative Analysis of ML Techniques for Data-Driven Anomaly Detection, Classification and Localization in Distribution System

High penetration of Distributed Energy Resources (DERs), fundamental load behavior changes, controllable loads, and significant increase in Electrical Vehicles (EVs) lead to complex dynamic behavior of the electric distribution system. Increasing number of components also means more measurements, more data and more data anomalies. Detecting, classifying and localizing these anomalies are important for situational awareness, and at the same time, very challenging given increasing complexity of the system. Highly accurate and high-resolution analytical techniques are needed to support anomaly detection, classification and localization (AD-C-L) for monitoring, root cause analysis and decision making. This paper provides comprehensive review and analysis of the existing spatio-temporal AD-C-L techniques within the distribution system. Challenges for specific problems in AD-C- L have been also discussed in this paper. Existing AD-C- L techniques have been categorized and synthesized for specific merits and limitations of multiple Machine Learning (ML) methodologies using common developed metrics of performance. The comparative analysis is summarized and presented with the open research challenges and path forward for future research needs.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Joint Estimation of Topology and Injection Statistics in Distribution Grids with Missing Nodes

Optimal operation of distribution grid resources relies on accurate estimation of its state and topology. Practical estimation of such quantities is complicated by the limited presence of real-time meters. This article discusses a theoretical framework to jointly estimate the operational topology and statistics of injections in radial distribution grids under limited availability of nodal voltage measurements. In particular, we show that our proposed algorithms are able to provably learn the exact grid topology and injection statistics at all unobserved nodes as long as they are not adjacent. The algorithm design is based on novel ordered trends in voltage magnitude fluctuations at node groups, that are independently of interest for radial physical flow networks. The complexity of the designed algorithms is theoretically analyzed and their performance is validated using both linearized and nonlinear ac power flow samples in test distribution grids.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Influence of metal ion complexation on the radiolytic longevity of butyramide extractants under direct dissolution conditions

The direct dissolution of volox-treated used nuclear fuel (UNF) into an organic solution—comprised of diluent and specialized extractants—poses a promising alternative to the traditional liquid-liquid solvent extraction approach to reprocessing UNF. However, moving to direct dissolution removes the presence of a concentrated nitric acid aqueous phase, which has been shown to significantly influence the radiolytic longevity of extractants in liquid-liquid solvent extraction flowsheets. With this in mind, and given the limited knowledge of radiation effects under direct dissolution conditions, we present a time-resolved and dose accumulation study on the impact of direct dissolution conditions on the radiolytic longevity of two candidate butyramide extractants—N,N-di-(2-ethylhexyl) butyramide (DEHBA) and N,N-di-(2-ethylhexyl)isobutyramide (DEHiBA)—in pre-equilibrated n-dodecane solvent in the presence and absence of process relevant metal ions, uranium and rhenium. Rhenium, and by extension technetium, extraction had little impact (=10%) on the overall radiolytic stability of these ligands, despite observed increases in chemical kinetic reactivity (>2×) of the corresponding complexes with the n-dodecane radical cation. Uranium-loading on the other hand, significantly improved the lifetime of both ligands (>30%) under gamma irradiation, with a greater stabilization observed for DEHBA over DEHiBA. This draft manuscript has been prepared in fulfillment of NTRD-MRWFD-2024 M3FT-24IN030101115.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗