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Internship Progress Summary: Fall 2016
This fall I had the opportunity to work at Los Alamos National Laboratory for the Technology Applications engineering group. I assisted two main projects during my appointment, both related to the Lab’s mission statement: “To solve national security challenges through scientific excellence.” My first project, a thermal source transfer unit, involved skills such as mechanical design, heat transfer simulation, and design analysis. The goal was to create a container that could protect a heat source and regulate its temperature during transit. I generated several designs, performed heat transfer simulations, and chose a design for prototyping. The second project was a soil drying unit for use in post blast sample analysis. To ensure fast and accurate sample processing, agents in the field wanted a system that could process wet dirt and turn it into dry powder. We designed a system of commercially available parts, and we tested the systems to determine the best methods and processes.
Analysis of backwash settings to maximize net water production in an engineering-scale ultrafiltration system for water reuse
Ultrafiltration (UF) has been widely utilized as water pretreatment for different applications especially in water reuse. The UF system operation is characterized by a filtration phase, where particles accumulate on the membrane surface resulting in an increase in the transmembrane pressure (TMP) and a cleaning phase, where foulants are removed through cleaning cycles including physical backwash and chemical-enhanced backwash (CEB). In this study, data from an engineering-scale UF system treating reclaimed wastewater were used to assess the impact of backwashing on the filtration process. TMP backwash trigger, backwash duration, and CEB frequency were purposely varied for a cycle-by-cycle investigation on the net water production, water recovery, initial operating TMP, and filtration cycle duration. As the TMP backwash trigger was varied between 62 and 145kPa, the maximum net water production (63 m 3 /d) was achieved at 103kPa and water recovery remained relatively constant at approximately 92%. Backwash durations of 45, 65, and 85s were performed where both net water production and water recovery yielded similar results (~63 m 3 /d and ~ 91%) compared with 103kPa TMP backwash trigger. The CEB frequency was also lowered from one every three backwashes (1/3) to 1/6 and 1/12 and resulted in decreased net water production and water recovery while the initial TMP increased. Interestingly, the total number of CEBs remained approximately constant regardless of their frequency. In conclusion, results suggest that CEB is an important fouling control process to maximize water production.
Systems Engineering Project - Tritium
The purpose of this project is to apply a systems engineering method to a programmatic improvement or implementation of a system found within the Weapons and Complex Integration (WCI) Nuclear Materials Technology Program (NMTP) at Lawrence Livermore National Laboratory (LLNL). This project identifies an opportunity for improvement of the Tritium Processing Station (TPS) based on key stakeholder requirements. This document will cover the generation of the selected concept, system operational context and use cases, the production of verifiable engineering requirements, functional decomposition, and an assessment of risk via a failure mode and effect analysis (FMEA).
Engineering Ultrathin Alloy Shell in Au@AuPd Core-Shell Nanoparticles for Efficient Plasmon-Driven Photocatalysis
Bimetallic core-shell nanoparticles (NPs) possessing a synergetic coupling of plasmonic and catalytic metals have emerged as promising prototypes for efficient plasmon-driven photocatalysis. Here, Au@AuPd core-shell NPs composed of Au core NP and ultrathin AuPd shell are introduced to acquire improved light utilization efficiency in photocatalytic selective oxidation. With systematical control of the composition of the ultrathin alloy shell, it reveals that the Au@AuPd core-shell NPs with 10 at% Pd (in the single-atom alloy regime) is an effective nanostructure capable of maximizing the quantum yield of plasmon-induced light absorption and optimizing the surface electronic structure for catalytic reactions. This controlled system provides new insights into shell engineering for enhancing photocatalytic performance via the regulation of energy funneling processes in core-shell nanocatalysts.
Harnessing expert knowledge: Defining a Bayesian network decision model with limited data-Model structure for the vibration qualification problem
As systems become more complex, systems engineers rely on experts to inform decisions. There are few experts and limited data in many complex new technologies. This challenges systems engineers as they strive to plan activities such as qualification in an environment where technical constraints are coupled with the traditional cost, risk, and schedule constraints. Bayesian network (BN) models provide a framework to aid systems engineers in planning qualification efforts with complex constraints by harnessing expert knowledge and incorporating technical factors. By quantifying causal factors, a BN model can provide data about the risk of implementing a decision supplemented with information on driving factors. This allows a systems engineer to make informed decisions and examine “what-if” scenarios. This paper discusses a novel process developed to define a BN model structure based primarily on expert knowledge supplemented with extremely limited data (25 data sets or less). The model was developed to aid qualification decisions—specifically to predict the suitability of six degrees of freedom (6DOF) vibration testing for qualification. The process defined the model structure with expert knowledge in an unbiased manner. Finally, validation during the process execution and of the model provided evidence the process may be an effective tool in harnessing expert knowledge for a BN model.
Automated System of Diagnostic Monitoring at Bureya HPP Hydraulic Engineering Installations: a New Level of Safety
This article presents the design, hardware, and software solutions developed and placed in service for the automated system of diagnostic monitoring (ASDM) for hydraulic engineering installations at the Bureya HPP, and assuring a reliable process for monitoring hydraulic engineering installations. Project implementation represents a timely solution of problems addressed by the hydraulic engineering installation diagnostics section.
Composite Robust $H_\infty$ Control for Uncertain Stochastic Nonlinear Systems with State Delay via Disturbance Observer
Here in this note, the robust stochastic stabilization and robust H_infinity control problems are investigated for uncertain stochastic time-delay systems with nonlinearity and multiple disturbances. By estimating the disturbance, which can be described by an exogenous model, a composite hierarchical control scheme is proposed that integrates the output of the disturbance observer with state feedback control law. Sufficient conditions for the existence of the disturbance observer and composite hierarchical controller are established in terms of linear matrix inequalities, which ensure the mean-square asymptotic stability of the resulting closed-loop system and the disturbance attenuation. It has been shown that the disturbance rejection performance can also be achieved. A numerical example is provided to show the potential of the proposed techniques and encouraging results have been obtained.
Assessment of turbulent combustion models for simulating pre-chamber ignition in a natural gas engine
Lean combustion in an internal combustion engine is a promising strategy to increase thermal efficiency by leveraging a more favorable specific heat ratio of the fresh mixture and simultaneously suppressing the heat losses to the cylinder wall. However, unstable ignition events and slow flame propagation at fuel-lean condition lead to high cycle-to-cycle variability and hence limit the high-efficiency engine operating range. Pre-chamber ignition is considered an effective concept to extend the lean operating limit, by providing spatially distributed ignition with multiple turbulent flame-jets and enabling faster combustion rate compared to the conventional spark ignition approach. From a numerical modeling perspective, to date, still the science base and available simulation tools are inadequate for understanding and predicting the combustion processes in pre-chamber ignited engines. In this paper, conceptually different RANS combustion models widely adopted in the engine modeling community were used to simulate the ignition and combustion processes in a medium-duty natural gas engine with a pre-chamber spark-ignition system. A flamelet-based turbulent combustion model, i.e., G-equation, and a multi-zone well-stirred reactor model were employed for the multi-dimensional study. Simulation results were compared with experimental data in terms of in-cylinder pressure and heat release rate. Finally, the analysis of the performance of the two models is carried out to highlight the strengths and limitations of the two formulations respectively.
MO-DE-206-00: Joint AAPM-WMIS Symposium: Metabolic Imaging of Cancer
In this symposium jointly sponsored by the World Molecular Imaging Society (WMIS) and the AAPM, luminary speakers on imaging metabolism will discuss three impactful topics. The first presentation on Cellular Metabolism of FDG will be given by Guillem Pratx (Stanford). This presentation will detail new work on looking at how the most common molecular imaging agent, fluoro-deoxy-glucose is metabolized at a cellular level. This will be followed by a talk on an improved approach to whole-body PET imaging by Simon Cherry (UC Davis). Simon’s work on a new whole-body PET imaging system promises to have dramatic improvement in our ability to detect and characterize cancer using PET. Finally, Jim Bankson (MD Anderson) will discuss extremely sophisticated approaches to quantifying hyperpolarized-13-C pyruvate metabolism using MR imaging. This technology promises to compliment the exquisite sensitivity of PET with an ability to measure not just uptake, but tumor metabolism. Learning Objectives: Understand the metabolism of FDG at a cellular level. Appreciate the engineering related to a novel new high-sensitivity whole-body PET imaging system. Understand the process of hyperpolarization, how pyruvate relates to metabolism and how advanced modeling can be used to better quantify this data. G. Pratx, Funding: 5R01CA186275, 1R21CA193001, and Damon Runyon Cancer Foundation. S. Cherry, National Institutes of Health; University of California, Davis; Siemens Medical SolutionsJ. Bankson, GE Healthcare; NCI P30-CA016672; CPRIT PR140021-P5.
MO-DE-206-01: Cellular Metabolism of FDG
In this symposium jointly sponsored by the World Molecular Imaging Society (WMIS) and the AAPM, luminary speakers on imaging metabolism will discuss three impactful topics. The first presentation on Cellular Metabolism of FDG will be given by Guillem Pratx (Stanford). This presentation will detail new work on looking at how the most common molecular imaging agent, fluoro-deoxy-glucose is metabolized at a cellular level. This will be followed by a talk on an improved approach to whole-body PET imaging by Simon Cherry (UC Davis). Simon’s work on a new whole-body PET imaging system promises to have dramatic improvement in our ability to detect and characterize cancer using PET. Finally, Jim Bankson (MD Anderson) will discuss extremely sophisticated approaches to quantifying hyperpolarized-13-C pyruvate metabolism using MR imaging. This technology promises to compliment the exquisite sensitivity of PET with an ability to measure not just uptake, but tumor metabolism. Learning Objectives: Understand the metabolism of FDG at a cellular level. Appreciate the engineering related to a novel new high-sensitivity whole-body PET imaging system. Understand the process of hyperpolarization, how pyruvate relates to metabolism and how advanced modeling can be used to better quantify this data. G. Pratx, Funding: 5R01CA186275, 1R21CA193001, and Damon Runyon Cancer Foundation. S. Cherry, National Institutes of Health; University of California, Davis; Siemens Medical SolutionsJ. Bankson, GE Healthcare; NCI P30-CA016672; CPRIT PR140021-P5.
MO-DE-206-02: Cellular Metabolism of FDG
In this symposium jointly sponsored by the World Molecular Imaging Society (WMIS) and the AAPM, luminary speakers on imaging metabolism will discuss three impactful topics. The first presentation on Cellular Metabolism of FDG will be given by Guillem Pratx (Stanford). This presentation will detail new work on looking at how the most common molecular imaging agent, fluoro-deoxy-glucose is metabolized at a cellular level. This will be followed by a talk on an improved approach to whole-body PET imaging by Simon Cherry (UC Davis). Simon’s work on a new whole-body PET imaging system promises to have dramatic improvement in our ability to detect and characterize cancer using PET. Finally, Jim Bankson (MD Anderson) will discuss extremely sophisticated approaches to quantifying hyperpolarized-13-C pyruvate metabolism using MR imaging. This technology promises to compliment the exquisite sensitivity of PET with an ability to measure not just uptake, but tumor metabolism. Learning Objectives: Understand the metabolism of FDG at a cellular level. Appreciate the engineering related to a novel new high-sensitivity whole-body PET imaging system. Understand the process of hyperpolarization, how pyruvate relates to metabolism and how advanced modeling can be used to better quantify this data. G. Pratx, Funding: 5R01CA186275, 1R21CA193001, and Damon Runyon Cancer Foundation. S. Cherry, National Institutes of Health; University of California, Davis; Siemens Medical SolutionsJ. Bankson, GE Healthcare; NCI P30-CA016672; CPRIT PR140021-P5.
MO-DE-206-03: Quantifying Metabolism with Hyperpolarized MR
In this symposium jointly sponsored by the World Molecular Imaging Society (WMIS) and the AAPM, luminary speakers on imaging metabolism will discuss three impactful topics. The first presentation on Cellular Metabolism of FDG will be given by Guillem Pratx (Stanford). This presentation will detail new work on looking at how the most common molecular imaging agent, fluoro-deoxy-glucose is metabolized at a cellular level. This will be followed by a talk on an improved approach to whole-body PET imaging by Simon Cherry (UC Davis). Simon’s work on a new whole-body PET imaging system promises to have dramatic improvement in our ability to detect and characterize cancer using PET. Finally, Jim Bankson (MD Anderson) will discuss extremely sophisticated approaches to quantifying hyperpolarized-13-C pyruvate metabolism using MR imaging. This technology promises to compliment the exquisite sensitivity of PET with an ability to measure not just uptake, but tumor metabolism. Learning Objectives: Understand the metabolism of FDG at a cellular level. Appreciate the engineering related to a novel new high-sensitivity whole-body PET imaging system. Understand the process of hyperpolarization, how pyruvate relates to metabolism and how advanced modeling can be used to better quantify this data. G. Pratx, Funding: 5R01CA186275, 1R21CA193001, and Damon Runyon Cancer Foundation. S. Cherry, National Institutes of Health; University of California, Davis; Siemens Medical SolutionsJ. Bankson, GE Healthcare; NCI P30-CA016672; CPRIT PR140021-P5.
Advanced combustion free-piston engines: A comprehensive review
A reciprocating engine without a crank-slider mechanism is called a free-piston engine. If the piston is directly connected to a linear alternator, it is called a free-piston linear alternator. Free-piston engines and free-piston linear alternators have the potential to offer solutions for future hybrid electric vehicles and stationary power generation, by enabling direct conversion of mechanical energy to electricity. They benefit from reduced friction losses compared to conventional engines and can have variable compression ratio, which enables combustion control and optimization. Their widespread application has been limited by the necessity for high-speed control strategies. However, their operating characteristics can provide high efficiency, especially when used with low temperature combustion strategies. Low temperature combustion combines the high thermal efficiency of diesel engines, with the low soot emissions of spark-ignition engines, and low NO x emissions because of low burned gas temperatures. This article provides a comprehensive review of free-piston engine technology, with a focus on advanced combustion processes and their potential for use in future powertrain systems.
LANL Hydrogen Processing Laboratory (HPL), Data acquisition and control system upgrade
This report describes upgrades made to the data acquisition and control system of the LANL hydrogen processing laboratory.
SMR Carbon Capture Design and TEA (Final Technical Report)
This project sought to select a process configuration, select a commercial technology offering, and complete an initial engineering design of a carbon capture system that recovers and ultimately would store ~190,000 tonnes per year of CO 2 with 90%+ carbon capture efficiency from an existing steam methane reforming (SMR) plant at Phillips 66’s Rodeo Refinery.
Colorado State University Extension Industrial Assessment Center
Since its inception in 1984, the Colorado State University Industrial Assessment Center has performed industrial assessments at more than 720 manufacturing facilities in Colorado, Montana, Nebraska, Nevada, New Mexico, North Dakota, South Dakota, Utah, and Wyoming. From 2017 to 2019 there was a funding gap and the IAC shutdown. In 2020 through DOE extension funding the University relaunched the IAC as an extension center in order to provide assessments to underserved areas. Under this award, the CSU Industrial Assessment Center (IAC) was rebuilt with the help of student employees and the director. The CSU team experienced difficulty as the program was in the process of being restarted right as the 2020 pandemic hit. Nonetheless, the CSU IAC was instrumental in providing energy assessments to manufacturers in Colorado and Wyoming during the period of performance of 09/2019 – 12/2022. The Department of Energy's Industrial Assessment Centers (IACs) provide a valuable service to small and medium-sized manufacturers seeking to optimize their operations. These university-based centers offer no-cost, on-site assessments conducted by engineering faculty and students, analyzing energy consumption, production processes, and waste streams. They utilize advanced data acquisition systems to record operational data, and then use the data to create assessment recommendations. These recommendations form the foundation of the comprehensive energy report. The comprehensive report delivers actionable recommendations for enhancing energy efficiency, reducing waste, and reducing greenhouse gas emissions and improving productivity, often identifying significant cost savings. Furthermore, IACs facilitate access to implementation grants, enabling the businesses to readily adopt these improvements. This program not only strengthens individual businesses but also contributes to national goals of training the next generation of energy experts, as well as increasing industrial competitiveness and reduced environmental impact.
Bridging Cloud and Edge Computing at NREL Using CONNECT: Cloud Optimized Networking for Next-Gen Edge Computing Technologies [Slides]
CONNECT is an innovative on-premise hardware and software solution that integrates edge and cloud computing infrastructure at NREL. Built on the AWS Greengrass middleware and leveraging the MQTT protocol, CONNECT enables real-time data streaming from IoT devices and gateways to both cloud and local services, empowering researchers to rapidly capture, analyze, and act upon edge-generated data while leveraging cloud capabilities. The platform addresses research infrastructure challenges by providing a pre-approved platform which is already configured with the correct networking and cybersecurity baselines thus eliminating procurement delays and enabling on-demand availability. CONNECT's hybrid architecture efficiently manages burstable workloads, allowing research teams to dynamically scale computational capacity, handle peak data loads, and reduce operational bottlenecks. Advanced capabilities include built-in GPU support for executing machine learning models which enables low-latency inference at the edge from models trained in the cloud. This architecture supports real-time analytics and filtering, providing a mechanism to allow only transmitting and processing high-value data. Cloud-based configuration management permits engineers to manage on-premise systems remotely, optimizing operational efficiency. By bridging edge and cloud computing, CONNECT provides NREL researchers with a flexible, scalable platform that accelerates scientific discovery while maintaining robust security and performance standards.