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At least 19 records

Using Parameter Sweep in WaterTAP to Analyze New Water Treatment Technologies

We describe a powerful and generalized parameter sweep tool in this report that was originally developed to analyze the performance of existing and novel water treatment models being developed in WaterTAP. Since WaterTAP is built upon IDAES and Pyomo, the parameter sweep tool can be used to systematically explore and debug the behavior of most Pyomo and IDAES numerical models. In order to enable meaningful analyses, the parameter sweep tool has been designed with the following features: 1) Model flexibility: The parameter sweep tool does not enforce any restrictions on the types of models that can be used with it. As long as a Pyomo model can be solved and the parameter is active and mutable, the tool only needs functions that describe how to run the model, the sweep parameters, and the output quantities of interest. 2) Flexible sampling: The parameter sweep tool has inbuilt functions to generate samples from a random distribution or a multidimensional Euclidean space. Furthermore, the users have to ability to supply samples generated from a tool of their choice. 3) Multiple sweep types: A user can choose from one of 3 types of parameter sweeps depending on their needs. 4) Detailed outputs: Outputs generated by the parameter sweep tool can be stored in detailed H5 file or user-friendly CSV files for post processing. 5) Parallel computing: The parameter sweep supports shared and distributed memory parallel computing to enable the use of high performance computers (HPC) for large-scale analyses. 6) Modular: The parameter sweep tool is self-contained and can easily be integrated within an outer-loop analysis or as desired by the user. 7) Ease of use: The tool is well documented and a simple sweep can be easily executed by following the online documentation in a few lines of code. We demonstrate the use of the parameter sweep tool on a simple water treatment system from the WaterTAP repository and show its parallel scaling performance on an Apple laptop and NREL's Eagle HPC. The parameter sweep tool is actively being used with models currently being developed within WaterTAP and we expect its use to grow beyond it to other IDAES and Pyomo models.

97 MATHEMATICS AND COMPUTING↗

IDAES-PSE 2.4.0 Release

The Institute for the Design of Advanced Energy Systems (IDAES) Integrated Platform is a versatile computational environment offering extensive process systems engineering (PSE) capabilities for optimizing the design and operation of complex, interacting technologies and systems. IDAES enables users to efficiently search vast, complex design spaces to discover the lowest cost, most environmentally sustainable solutions while supporting the full process modeling lifecycle, from conceptual design to dynamic optimization and control. The extensible, open platform empowers users to create models of novel processes and rapidly develop custom analyses, workflows, and end-user applications.. Deprecations • Convergence Analysis tool (idaes/core/util/convergence): deprecated in favor of new Parameter Sweep tools. To be removed in v3.0.0. New Beta Capabilities • Parameter Sweep Tool (idaes.core.util.parameter_sweep) o A new API for defining and performing parameter sweep studies on IDAES models has been developed • Diagnostics Tools (idaes.core.util.model_diagnostics) o New methods for identifying duplicate variables and constraints have been added to the diagnostics toolbox o New tools for detecting ill conditioning in Jacobians have been developed and are available in the model_diagnostics module. These provide alternatives to the existing DegeneracyHunter toolbox, and will eventually be merged with this capability, but initial working versions have been provided as beta capabilities for interested users o IpoptConvergenceAnalysis (replaces deprecated Convergence Analysis tool):  A new tool for performing convergence analysis studies that leverages the new Parameter Sweep tools has been developed. This tool allows users to define the input parameters to their model and sampling methods for these (leveraging Pysmo's sampling tools) and to then solve their model across the sampled domains and return a summary of the solver performance (IPOPT only) Improved Models • Thickener model (idaes.models.unit_models.solid_liquid.thickener) o Improved model to include predictive correlations for unit sizing based on settling velocity measurements (steady-state only) • Modular Property Packages o Added general support for calculating critical properties of mixtures using defined Equation of State modules. New API defined for Equation of State modules in order to define the necessary constraints for calculating critical properties (most EoS modules DO NOT support calculation of critical properties (yet)) o Added new methods to Cubic Equation of State module to support calculation of critical properties

DiagnosticsToolbox↗

From TPL assessment to design optimization: Wave energy converter control co-design applied to the RM3

The Reference Model (RM) project developed six marine energy converter concepts using a sequential design methodology, which, while widely adopted in the industry, often overlooks interactions between system components, resulting in suboptimal designs. One such example is the Reference Model 3 (RM3), a two-body point absorber wave energy converter (WEC). An assessment using the Technology Performance Level (TPL) revealed that RM3’s low power-to-cost ratio, partly due to expensive steel construction, limits its techno-economic performance. Here, this study aims to redesign RM3 by reducing its scale and employing control co-design to integrate WEC and Power Take-Off (PTO) dynamics, constraints, and cost considerations within an optimization framework. We demonstrate the limitations of RM3’s current PTO design and explore the benefits of scaling down to enhance techno-economic viability by lowering material costs. Using WecOptTool, we conduct a parameter sweep over gear ratios and spring stiffnesses for various Commercial Off-The-Shelf generators in irregular wave conditions. Our findings emphasize the importance of aligning PTO components with WEC dynamics, showing that control co-design and strategic scaling can improve RM3’s power-to-cost ratio. This study presents a transferable example of applied control co-design for other WECs, supporting early-stage developers in their design decisions.

Off the shelf components↗

Dynamic machine learning-based optimization algorithm to improve boiler efficiency

With decreasing computational costs, improvement in algorithms, and the aggregation of large industrial and commercial datasets, machine learning is becoming a ubiquitous tool for process and business innovations. Machine learning is still lacking applications in the field of dynamic optimization for real-time control. This work presents a novel framework for performing constrained dynamic optimization using a recurrent neural network model combined with a metaheuristic optimizer. The framework is designed to augment an existing control system and is purely data-driven, like most industrial Model Predictive Control applications. Several recurrent neural network models are compared as well as several metaheuristic optimizers. Hyperparameters and optimizer parameters are tuned with parameter sweeps, and the resulting values are reported. Further, the best parameters for each optimizer and model combination are demonstrated in closed-loop control of a dynamic simulation, and several recommendations are made for generalizing this framework to other systems. Up to 0.953% improvement is realized over the non-optimized case for a simulated coal-fired boiler. While this is not a large improvement in percentage, the total economic impact is $991,000 per year, and this study builds a foundation for future machine learning with dynamic optimization.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

High-dimensional control co-design of a wave energy converter with a novel pitch resonator power takeoff system

Researchers are exploring adding wave energy converters to existing oceanographic buoys to provide a predictable source of renewable power. A ”pitch resonator” power take-off system has been developed that generates power using a geared flywheel system designed to match resonance with the pitching motion of the buoy. However, the novelty of the concept leaves researchers uncertain about various design aspects of the system. This work presents a novel design study of a pitch resonator to inform design decisions for an upcoming deployment of the system. The assessment uses control co-design via WecOptTool to optimize control trajectories for maximal electrical power production while varying five design parameters of the pitch resonator. Given the large search space of the problem, the control trajectories are optimized within a Monte Carlo analysis to identify optimal designs, followed by parameter sweeps around the optimum to identify trends between the design parameters. The gear ratio between the pitch resonator spring and flywheel are found to be the most sensitive design variables to power performance. Finally, the assessment also finds similar power generation for various sizes of resonator components, suggesting that correctly designing for optimal control trajectories at resonance is more critical to the design than component sizing.

16 TIDAL AND WAVE POWER↗

A method for examining ensemble averaging forms during the transition to turbulence in HED systems for application to RANS models

This paper discusses a strategy to initialize a two-dimensional (2D) Reynolds-averaged Navier–Stokes model [LANL's Besnard–Harlow–Rauenzahn (BHR) model] in order to describe an unsteady transitional Richtmyer–Meshkov (RM)-induced flow observed in on-going high-energy-density ensemble experiments performed on the OMEGA-EP facility. The experiments consist of a nominal single-mode perturbation (initial amplitude a 0 ≈ 10 and wavelength $λ$ = 100μm) with target-to-target variations in the surface roughness subjected to the RM instability with delayed Rayleigh–Taylor in a heavy-to-light configuration. Our strategy leverages high-resolution three-dimensional (3D) implicit large eddy simulations (ILES) simulations to initialize BHR-relevant parameters and subsequently validate the 2D BHR results against the 3D ILES simulations. A suite of five 3D ILES simulations corresponding to five experimental target profiles is undertaken to generate an ensemble dataset. Using ensemble averages from the 3D simulations to initialize the turbulent kinetic energy in the BHR model ( K 0 ) demonstrates the ability of the model to predict the time evolution of the interface as well as the density-specific-volume covariance, b . To quantify the sensitivity of the BHR results to the choice of K 0 and the initial turbulent length scale, S 0 , we execute a parameter sweep spanning four orders of magnitude for both S 0 and K 0 , generating a parameter space consisting of 26 simulations. The Pearson's correlation coefficient is used as a measure of discrepancy between the 2D BHR and 3D ILES simulations and reveals that the ranges 8≲S 0 ≲20 μm and 10 9 ≲K 0 ≲10 10 cm 2 /s 2 produce predictions that agree best with the 3D ILES results.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Parametric tip effects for conformable rotor applications

A research study was initiated to systematically determine the impact of selected blade tip geometric parameters on aeroelasticity conformable rotor performance and loads characteristics. The model articulated rotors included baseline and torsionally soft blades with interchangeable tips. Seven blade tip designs were evaluated on the baseline rotor and three tip designs were tested on the torsionally soft blades. The designs incorporated a systematic variation in three geometric parameters: sweep, taper, and anhedral. The rotors were evaluated in the NASA Langley Transonic Dynamics Tunnel at several advance ratios, lift and propulsive force values, and tip Mach numbers. Based on the test results, tip parameter variations generated significant rotor performance and loads difference for both baseline and torsionally soft blades. Azimuthal variation of elastic twist generated by the tip parameters strongly correlated with rotor performance and loads, but the magnitude of advancing blade elastic twist did not correlate.

Mantay, W. R.↗

Effect of ohmic, mass-transfer, and kinetic resistances on linear-sweep voltammetry in a cylindrical-pore electrode

A means is presented to account for the effect of ohmic, mass-transfer, and kinetic resistances on linear-sweep voltammograms by modeling a pore in a porous matrix as a cylindrical-pore electrode, and solving the mass and charge conservation equations in the context of this geometry for the simply redox reaction O + ne(-) yield R where both O and R are soluble species. Both analytical and numerical techniques are used to solve the governing equations. The calculated peak currents and potentials are correlated by empirical formulas to the measurable parameters: sweep rate, concentration of the redox species, diffusion coefficient, conductivity of the electrolyte, and pore dimensions. Using the correlations, a methodology is established for determining if the redox reaction kinetics are irreversible or reversible (Nernstian). If the reaction is irreversible, it is shown how the standard rate constant and the transfer coefficient may be extracted from linear-sweep voltammetry data, or, if the reaction is reversible, how the number of electrons transferred may be deduced.

Weidner, John W.↗

Satellite sweeping of electrons at Neptune and Uranus

Knowledge of satellite sweeping parameters at Neptune and Uranus, and of their functional dependences on particle energy and pitch angle, can be critical in the proper identification of parent absorbers for observed absorption signatures in regions where OTD (offset, tilted dipole) models are valid representations of the measured magnetic fields. In this paper, critical electron energies are calculated for longitudinal drift resonance, snowplow (i.e., strong) absorption, leapfrog, and corkscrew effects, using a reduced version of OTD that neglects nonaxial dipole offsets. Earlier analytic work on sweeping rates is extended to give the radial dependence of these rates within the minimum-L region and to set limits on diffusion of electrons with the simplifying approximation that leapfrog effects are ignored.

Cooper, John F.↗

SE-FIT

The mathematical theory of capillary surfaces has developed steadily over the centuries, but it was not until the last few decades that new technologies have put a more urgent demand on a substantially more qualitative and quantitative understanding of phenomena relating to capillarity in general. So far, the new theory development successfully predicts the behavior of capillary surfaces for special cases. However, an efficient quantitative mathematical prediction of capillary phenomena related to the shape and stability of geometrically complex equilibrium capillary surfaces remains a significant challenge. As one of many numerical tools, the open-source Surface Evolver (SE) algorithm has played an important role over the last two decades. The current effort was undertaken to provide a front-end to enhance the accessibility of SE for the purposes of design and analysis. Like SE, the new code is open-source and will remain under development for the foreseeable future. The ultimate goal of the current Surface Evolver Fluid Interface Tool (SEFIT) development is to build a fully integrated front-end with a set of graphical user interface (GUI) elements. Such a front-end enables the access to functionalities that are developed along with the GUIs to deal with pre-processing, convergence computation operation, and post-processing. In other words, SE-FIT is not just a GUI front-end, but an integrated environment that can perform sophisticated computational tasks, e.g. importing industry standard file formats and employing parameter sweep functions, which are both lacking in SE, and require minimal interaction by the user. These functions are created using a mixture of Visual Basic and the SE script language. These form the foundation for a high-performance front-end that substantially simplifies use without sacrificing the proven capabilities of SE. The real power of SE-FIT lies in its automated pre-processing, pre-defined geometries, convergence computation operation, computational diagnostic tools, and crash-handling capabilities to sustain extensive computations. SE-FIT performance is enabled by its so-called file-layer mechanism. During the early stages of SE-FIT development, it became necessary to modify the original SE code to enable capabilities required for an enhanced and synchronized communication. To this end, a file-layer was created that serves as a command buffer to ensure a continuous and sequential execution of commands sent from the front-end to SE. It also establishes a proper means for handling crashes. The file layer logs input commands and SE output; it also supports user interruption requests, back and forward operation (i.e. undo and redo), and others. It especially enables the batch mode computation of a series of equilibrium surfaces and the searching of critical parameter values in studying the stability of capillary surfaces. In this way, the modified SE significantly extends the capabilities of the original SE.

Chen, Yongkang↗

Modification of Jet Velocities in an Explosively Loaded Copper Target with a Conical Cavity

Here, in this work, the design and execution of an experiment with the goal of demonstrating control over the evolution of a copper jet is described. Simulations show that when using simple multi-material buffers placed between a copper target with a conical cavity and a cylinder of high-explosive, a variety of jetting behaviors occur based on material placement, including both jet velocity augmentation and mitigation. A parameter sweep was performed to determine optimal buffer designs in two configurations. Experiments using the optimal buffer designs verified the effectiveness of the buffers at altering jet velocities. Similar trends were shown between the experimental results and the modeling.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Optimizing Process Conditions during Catalytic Fast Pyrolysis of Pine with Pt/TiO 2 —Improving the Viability of a Multiple-Fixed-Bed Configuration

Catalytic fast pyrolysis (CFP) has been identified as a promising pathway for the production of renewable fuels and co-products. However, continued technology development is needed to increase process efficiency and reduce process costs. This report builds upon previous research in which a bifunctional metal–acid Pt/TiO 2 catalyst was utilized in a fixed-bed reactor operated with co-fed H 2 to improve product yield and reduce coke generation compared to conventional CFP methods. Here, we report further process optimization, in which we achieved similar CFP oil carbon efficiency (>35%) and CFP oil oxygen content (<20 wt %) to our previous report while reducing catalyst and equipment costs by increasing time-on-stream between regenerations by 40–95% and decreasing required regeneration time by more than a factor of 2. These process improvements were achieved by conducting parameter sweeps to determine optimum conditions for CFP and regeneration with key variables including pyrolysis temperature, catalytic upgrading temperature, hydrogen partial pressure, and regeneration oxygen concentration. Coupled with comprehensive oil analyses, these data provide foundational insight into the deoxygenation and coking chemistries for CFP under realistic process conditions while also advancing the technology through applied engineering.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

High-throughput, in situ imaging of multi-layer powder-blown directed energy deposition with angled nozzle

Laser metal additive manufacturing (AM) has become an increasingly popular technology due to its flexibility in geometry and materials. As one of the commercialized additive processes, powder-blown directed energy deposition (DED) has been used in multiple industries such as aerospace, automotive, medical device, etc. However, a lack of fundamental understanding remains for this process, and many opportunities for alloy development and implementation can be identified. A high-throughput, in situ DED system capable of multi-layer builds that can address these issues is presented here. In this work, implications of layer heights and energy density are investigated through an extensive process parameter sweep, showcasing the power of a high-throughput setup while also discussing multi-layer interactions.

47 OTHER INSTRUMENTATION↗

Validating and optimizing mismatch tolerance of Doppler backscattering measurements with the beam model (invited)

In this work, we use the beam model of Doppler backscattering (DBS), which was previously derived from beam tracing and the reciprocity theorem, to shed light on mismatch attenuation. This attenuation of the backscattered signal occurs when the wavevector of the probe beam’s electric field is not in the plane perpendicular to the magnetic field. Correcting for this effect is important for determining the amplitude of the actual density fluctuations. Previous preliminary comparisons between the model and Mega-Ampere Spherical Tokamak (MAST) plasmas were promising. In this work, we quantitatively account for this effect on DIII-D, a conventional tokamak. We compare the predicted and measured mismatch attenuation in various DIII-D, MAST, and MAST-U plasmas, showing that the beam model is applicable in a wide variety of situations. Finally, we performed a preliminary parameter sweep and found that the mismatch tolerance can be improved by optimizing the probe beam’s width and curvature at launch. This is potentially a design consideration for new DBS systems.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Minimizing CGYRO HPC Communication Costs in Ensembles with XGYRO by Sharing the Collisional Constant Tensor Structure

First-principles fusion plasma simulations are both compute and memory intensive, and CGYRO is no exception. The use of many HPC nodes to fit the problem in the available memory thus results in significant communication overhead, which is hard to avoid for any single simulation. That said, most fusion studies are composed of ensembles of simulations, so we developed a new tool, named XGYRO, that executes a whole ensemble of CGYRO simulations as a single HPC job. By treating the ensemble as a unit, XGYRO can alter the global buffer distribution logic and apply optimizations that are not feasible on any single simulation, but only on the ensemble as a whole. The main saving comes from the sharing of the collisional constant tensor structure, since its values are typically identical between parameter-sweep simulations. This data structure dominates the memory consumption of CGYRO simulations, so distributing it among the whole ensemble results in drastic memory savings for each simulation, which in turn results in overall lower communication overhead.

CGYRO↗

ODI notebook additive_manufacturing_video_2022

Additive Manufacturing, video dataset Two-photon lithography (TPL) is a widely used 3D nanoprinting technique that uses laser light to create objects. Challenges to large-scale adoption of this additive manufacturing method include identifying light dosage parameters and monitoring during fabrication. A research team from LLNL, Iowa State University, and Georgia Tech is applying machine learning models to tackle these challenges-i.e., accelerate the process of identifying optimal light dosage parameters and automate the detection of part quality. Funded by LLNL's Laboratory Directed Research and Development Program, the project team has curated a video dataset of TPL processes for parameters such as light dosages, photo-curable resins, and structures. Both raw and labeled versions of the datasets are available on the links in the Open Data Initiative page. The code uses the labeled dataset. Notebook compiled by Nisha Mulakken (mulakken1@llnl.gov) for LLNL Open Data Initiative, Summer 2022. Original code provided by research team. Publications: X.Y. Lee, S.K. Saha, S. Sarkar, B. Giera. "Automated detection of part quality during two-photon lithography via deep learning." Additive Manufacturing 36, December 2020: doi.org/10.1016/j.addma.2020.101444 X.Y. Lee, S.K. Saha, S. Sarkar, B. Giera. "wo Photon lithography additive manufacturing: Video dataset of parameter sweep of light dosages, photo-curable resins, and structures." Data in Brief 32, October 2020. doi.org/10.1016/j.dib.2020.106119.

Mulakken, NishaJ↗