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At least 1,117 records · Page 62
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Off-line tracking of series parameters in distribution systems using AMI data

Electric distribution systems have historically lacked measurement points, and equipment is often operated to its failure point, resulting in customer outages. The widespread deployment of sensors at the distribution level is enabling observability. This paper presents an off-line parameter value tracking procedure that takes advantage of the increasing number of measurement devices being deployed at the distribution level to estimate changes in series impedance parameter values over time. The tracking of parameter values enables non-diurnal and non-seasonal change to be flagged for investigation. The presented method uses an unbalanced Distribution System State Estimation (DSSE) and a measurement residual-based parameter estimation procedure. Measurement residuals from multiple measurement snapshots are combined in order to increase the effective local redundancy and improve the robustness of the calculations in the presence of measurement noise. Data from devices on the primary distribution system and from customer meters, via an AMI system, form the input data set. Results of simulations on the IEEE 13-Node Test Feeder are presented to illustrate the proposed approach applied to changes in series impedance parameters. A 5% change in series resistance elements can be detected in the presence of 2% measurement error when combining less than 1 day of measurement snapshots into a single estimate.

Williams, Tess L.↗
DOE OSTI2022

Supply sunspots and shadows: Business siting patterns and inequitable rooftop solar adoption in the United States

Entrepreneurs in certain industries tend to locate new businesses in relatively affluent areas. Preferences to site businesses in affluent areas can reduce low-income household access to certain products. Some argue that business siting patterns could explain inequitable consumption patterns, though such causal claims are often empirically weak. Here, we explore whether business siting patterns partly explain inequitable adoption of rooftop solar photovoltaics in California. We show that solar business formation drives an immediate and sustained increase in local solar adoption, including in low-income areas. However, solar business siting patterns have only weak impacts on solar adoption equity. The data show how solar businesses headquartered in low-income areas nonetheless install solar for relatively affluent customers. Customer-level adoption inequity partly offsets the potential equity gains of siting more businesses in low-income areas. We discuss how the emergent nature and unique business model of rooftop solar help explain these nuanced results.

14 SOLAR ENERGY↗
DOE OSTI2023

Reviewing flexibility in industrial electrification: Focusing on green ammonia and steel in the United States

The renewable energy transition in the power sector involves a paradigm shift for flexibility. Flexible demand is more attainable than before, while supply flexibility faces new constraints due to the increased share of variable renewable resources. Increased demand flexibility can allow less use of peaking power plants and avoid need for additional capacity. Industrial flexibility could be especially interesting in this regard, as industrial customers are larger on average than other customers and have typically provided the largest share of demand response in the United States. We consider industrial demand, studying characteristics of flexible industrial loads. We then examine the dynamics of change occurring around industrial load flexibility by focusing on two case studies: green ammonia and steel production via electric arc furnaces. Electric arc furnace steel production is an important component of current demand response programs, whereas green ammonia and green fuels offer new paradigms for flexibility. We analyze the structure and functions of the technological innovation systems of load flexibility in those two industries via interviews with twenty-two stakeholders. Here, we conclude that in the United States these technological innovation systems are not well-functioning for industry in general or for steel, but do seem to be present for green ammonia. Additionally, explicit connections between scope two greenhouse gas emissions (those from purchased energy) and flexibility are lacking, and likewise industry stakeholders do not appear to make a connection between decarbonization and load flexibility, thus flexible demand is not viewed as a tool in industrial decarbonization.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

Assessment of human nuclear and mitochondrial DNA qPCR assays for quantification accuracy utilizing NIST SRM 2372a

In forensic DNA casework, a highly accurate real-time quantitative polymerase chain reaction (qPCR) assay is recommended per the Scientific Working Group on DNA Analysis Methods (SWGDAM) (SWGDAM Validation Guidelines for DNA Analysis Methods [1]) to determine whether a DNA sample is of sufficient quantity and robust quality to move forward with downstream short tandem repeats (STR) or sequencing analyses. Most of these assays rely on a standard curve, referred to herein and traditionally as absolute qPCR, in which an unknown is compared, relative to that curve. However, one fundamental issue with absolute qPCR is the quantifiable concentration of commercial assay standards can vary depending on (1) origin, i.e., whether from a cell line or a human subject, (2) supplier, (3) lot number, (4) shipping method, etc. In 2018, the National Institute for Standards and Technology (NIST) released a human DNA standard reference material for evaluating qPCR quantification standards, Standard Reference Material (SRM) 2372a, Romsos et al. (2018) [2] which contains three well-characterized human genomic DNA samples: Component A) a single male1 donor, Component B) a single female 1 donor, and Component C) a 1:3 male 2 :female 2 donor, each with certification data for nDNA and informational mitochondrial DNA(mtDNA)/nuclear DNA (nDNA) ratio data. The SRM 2372a was used to assess four qPCR assays: (1) Quantifiler Trio (Thermo Fisher Scientific, Waltham, MA) for nDNA quantification, (2) NovaQUANT (EMD Millipore Corporation, San Diego, CA) for nDNA and mtDNA quantification, (3) a custom duplex mtDNA assay, and (4) a custom triplex mtDNA assay. Additionally, extracts from eighteen (18) skeletal remains were tested with the latter three assays for concordance of DNA concentration and with assays (2) and (3), for the degradation state. Our assessment revealed that an accurate, efficient, and reproducible qPCR assay is dependent on (1) the quality and reliability of the DNA standard, (2) the qPCR chemistry, and (3) the specific primers, and probes (if applicable), used in an assay. Finally, our findings indicate qPCR assays may not always quantify as expected and that performance of each lot should be verified using a well-characterized DNA standard such as the NIST SRM 2372a and adjusted if warranted.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Analyzing inference workloads for spatiotemporal modeling

Ensuring power grid resiliency, forecasting climate conditions, and optimization of transportation infrastructure are some of the many application areas where data is collected in both space and time. Spatiotemporal modeling is about modeling those patterns for forecasting future trends and carrying out critical decision-making by leveraging machine learning/deep learning. Once trained offline, field deployment of trained models for near real-time inference could be challenging because performance can vary significantly depending on the environment, available compute resources and tolerance to ambiguity in results. Users deploying spatiotemporal models for solving complex problems can benefit from analytical studies considering a plethora of system adaptations to understand the associated performance-quality trade-offs. To facilitate the co-design of next-generation hardware architectures for field deployment of trained models, it is critical to characterize the workloads of these deep learning (DL) applications during inference and assess their computational patterns at different levels of the execution stack. In this paper, we develop several variants of deep learning applications that use spatiotemporal data from dynamical systems. We study the associated computational patterns for inference workloads at different levels, considering relevant models (Long short-term Memory, Convolutional Neural Network and Spatio-Temporal Graph Convolution Network), DL frameworks (Tensorflow and PyTorch), precision (FP16, FP32, AMP, INT16 and INT8), inference runtime (ONNX and AI Template), post-training quantization (TensorRT) and platforms (Nvidia DGX A100 and Sambanova SN10 RDU). Overall, our findings indicate that although there is potential in mixed-precision models and post-training quantization for spatiotemporal modeling, extracting efficiency from contemporary GPU systems might be challenging. Instead, co-designing custom accelerators by leveraging optimized High Level Synthesis frameworks (such as SODA High-Level Synthesizer for customized FPGA/ASIC targets) can make workload-specific adjustments to enhance the efficiency.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Roadmap and Benchmarking: Privacy in Federated Load Forecasting

Data-driven techniques for energy demand forecasting continue to emerge with promising impacts on distribution grid planning. However, the development of robust and generalizable machine learning models requires that representative high quality training data are available. Distributed energy resources have begun to embed intelligence, gathering large amounts of data on customer demand, behavior, and household devices that are connected to the grid. Though utilities aggregate meter-level demand data for load shaping, demand response, outage management, reliability planning, and billing applications, there lies an inherent privacy concern in sharing consumption data that may identify individual consumer behavioral patterns. Hence, while sharing the data is crucial, the private sensitive customer data must be safeguarded from being exposed or manipulated. In this study, we propose a roadmap for implementing a based privacy preserving framework to support the advancement of data-driven analytics in data-sensitive distributed energy resources environments. The roadmap incorporates federated learning–a distributed training framework, differential privacy–a statistical framework that provides guarantees to safeguard the leakage of sensitive data, secure multiparty computation and homomorphic encryption– techniques for encrypting model gradients and applying secure aggregation on the server. Moreover, we perform baseline experiments on the federated short-term load forecasting (STLF) task using open-source residential load profile datasets, offering insights into the challenges of integrating differential privacy into federated learning.

Abebe, Waqwoya [Oak Ridge National Laboratory (ORN↗
DOE OSTI2023

Functional variability in specific root respiration translates to autotrophic differences in soil respiration in a temperate deciduous forest

CO 2 release from forest soils (R s ) is a prominent flux in the global carbon cycle. Rs is derived from roots (autotrophic respiration, R a ) and microbial (heterotrophic) respiration and is highly dynamic, as it depends on edaphic and environmental conditions as well as root functional traits and microbial community composition. It is unclear how root functional traits affect root and microbial respiration rates; however, their consideration may help parse out the relative contributions of root and microbial respiration to R s . At a temperate forest site, root systems of 3–4 functional root orders and their surrounding surface soil were carefully excavated and placed into custom trays designed to repeatedly measure R s in situ on eight temperate tree species that varied in their root functional strategies and mycorrhizal affinity. R s was measured bi-weekly to monthly for nearly one year using a custom chamber attached to a gas exchange system. R s varied over time, ranging from 0.3 to 12 µmol m -2 s -1 . Comparable root systems of the same species were excised from the soil and specific root respiration rates (R r ) were measured. Rr ranged from 2.5 to 9.0 nmol g -1 s -1 and was negatively correlated with root tissue density and positively related to root tissue nitrogen concentration. Using R r to estimate R a , we estimate that R a accounts for <10%, on average 2–3%, of R s for individual root systems (averaging 1.2 g dry biomass) housed in surrounding soil (average 1.3 kg dry mass) in situ; thus, Ra was roughly 20 times greater than Rh per unit mass. The contribution of R a peaked in the fall and coincided with leaf senescence of the forest canopy. A soil-sterilizing experimental treatment designed to help isolate R a in situ reduced bacterial biomass and shifted fungal community composition, but there was no reduction in Rs of the in-situ root-soil tray systems. The relative R a to R s ratio increased with root functional strategies characterized by greater specific root length and tip abundance, but also to greater root tissue density. The ratio of R a to R s also increased with warmer soil temperatures and decreased slightly with increasing soil moisture. We discuss how incorporating root functional traits as modulators of the autotrophic contribution to R s could be considered when modeling total soil CO 2 efflux from forests.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Medium-scale to large-scale implementation of cyber-physical human experiments in live traffic

Autonomous Vehicles (AVs) such as cars and trucks are being developed and tested as Cyber-Physical Human systems while the technology improves. Before these systems can achieve full autonomy, some serve as tools in the form of adaptive cruise control. The CIRCLES Consortium investigates the potential for AVs to increase fuel efficiency of highway traffic by smoothing “stop-and-go” traffic waves that result from normal human driving behavior in congestion. We have performed an experiment to evaluate the real world effects of implementing this strategy. A medium-scale experiment was performed on I-24 near Nashville, TN in August 2021. This was a precursor to a larger experiment that will take place November 2022. We examine how the human part of the experiment will change as we scale up from an 11 vehicle test (four AVs) to 100 AVs. There are many solutions to problems of the medium-scale experiment that would be inconvenient, complicate the experience, or not be practicable. The medium-scale experiment involved 11 cars of which four had a custom control algorithm installed to be engaged by the driver. The large-scale experiment will have 100 cars, all with custom control algorithm installed to act on traffic when the controller is engaged. We examine key choices made for the medium experiment, and how some will be different for the large experiment. Our experience performing the medium-scale experiment has made it clear that repeating our methods from this smaller one are inefficient or impossible if used for the large-scale experiment and will be improved.

McQuade, Sean T.↗
DOE OSTI2021

Co-simulation of transactive energy markets: A framework for market testing and evaluation

The proliferation of distributed energy resources (DER)—and the ability to intelligently control these assets—is re-defining the electrical distribution system. As the number of controllable devices rapidly expands, grid operators must determine how to incorporate these assets while delivering reliable, equitable, and affordable electricity. One possible approach is to establish distribution-level electricity markets and allow devices/aggregations of devices to participate in price establishment. While this approach purports some of the same benefits as the highly successful wholesale electricity markets (i.e., open competition, efficient price discovery, reduced communication overhead), this needs to be researched and quantified via an analysis platform that models distribution-level markets at the appropriate fidelity. Specifically, the simultaneous evaluation of market performance, DER performance, DER bidding approaches, and distribution feeder power quality requires modeling that spans multiple technical areas. Co-simulation has emerged as a powerful tool in addressing this type of problem, where outputs depend on a range of underlying areas of expertise and associated models. In this paper we describe a solution, as implemented in the HELICS co-simulation platform, where we include (1) high fidelity house models, (2) intelligent bidding agents, (3) a modular market integration/design, and (4) a distribution feeder model. We then present a case study where we test two different market designs: (1) a pseudo-wholesale double-blind auction, and (2) an asynchronous matching market. In this work, the markets are run under two DER penetration levels and economic results are compared to full retail net energy metering and avoided cost net metering scenarios that bookend current approaches to remuneration of DER participation. We show the potential for transactive markets to provide increased value for most customers relative to net metering (and all customers relative to avoided cost scenarios) while decreasing costs for the utility.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2015

Brachytherapy Application With In Situ Dose Painting Administered by Gold Nanoparticle Eluters

Purpose: Recent studies show promise that administering gold nanoparticles (GNP) to tumor cells during brachytherapy could significantly enhance radiation damage to the tumor. A new strategy proposed for sustained administration of the GNP in prostate tumors is to load them into routinely used brachytherapy spacers for customizable in situ release after implantation. This in silico study investigated the intratumor biodistribution and corresponding dose enhancement over time due to GNP released from such GNP-loaded brachytherapy spacers (GBS). Method and Materials: An experimentally determined intratumoral diffusion coefficient (D) for 10-nm nanoparticles was used to estimate D for other sizes by using the Stokes-Einstein equation. GNP concentration profiles, obtained using D, were then used to calculate the corresponding dose enhancement factor (DEF) for each tumor voxel, using dose painting-by-numbers approach, for times relevant to the considered brachytherapy sources' lifetimes. The investigation was carried out as a function of GNP size for the clinically applicable low-dose-rate brachytherapy sources iodine-125 (I-125), palladium-103 (Pd-103), and cesium-131 (Cs-131). Results: Results showed that dose enhancement to tumor voxels and subvolumes during brachytherapy can be customized by varying the size of GNP released or eluted from the GBS. For example, using a concentration of 7 mg/g GNP, significant DEF (>20%) could be achieved 5 mm from a GBS after 5, 12, 25, 46, 72, 120, and 195 days, respectively, for GNP sizes of 2, 5, 10, 20, 30, and 50 nm and for 80 nm when treating with I-125. Conclusions: Analyses showed that using Cs-131 provides the highest dose enhancement to tumor voxels. However, given its relatively longer half-life, I-125 presents the most flexibility for customizing the dose enhancement as a function of GNP size. These findings provide a useful reference for further work toward development of potential new brachytherapy application with in situ dose painting administered via gold nanoparticle eluters for prostate cancer.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2016

A Novel Form of Breast Intraoperative Radiation Therapy With CT-Guided High-Dose-Rate Brachytherapy: Results of a Prospective Phase 1 Clinical Trial

Purpose: Existing intraoperative radiation therapy (IORT) techniques are criticized for the lack of image guided treatment planning and energy deposition with, at times, poor resultant dosimetry and low radiation dose. We pioneered a novel method of IORT that incorporates customized, computed tomography (CT)-based treatment planning and high-dose-rate (HDR) brachytherapy to overcome these drawbacks: CT-HDR-IORT. Methods and Materials: A phase 1 study was conducted to demonstrate the feasibility and safety of CT-HDR-IORT. Eligibility criteria included age ≥50 years, invasive or in situ breast cancer, tumor size <3 cm, and N0 disease. Patients were eligible before or within 30 days of breast-conserving surgery (BCS). BCS was performed, and a multilumen balloon catheter was placed. CT images were obtained, a customized HDR brachytherapy plan was created, and a dose of 12.5 Gy was delivered to 1-cm depth from the balloon surface. The catheter was removed, and the skin was closed. The primary endpoints were feasibility and acute toxicity. Feasibility was defined as IORT treatment interval (time from CT acquisition until IORT completion) ≤90 minutes. The secondary endpoints included dosimetry, cosmetic outcome, quality of life, and late toxicity. Results: Twenty-eight patients were enrolled. The 6-month follow-up assessments were completed by 93% of enrollees. The median IORT treatment interval was 67.2 minutes (range, 50-108 minutes). The treatment met feasibility criteria in 26 women (93%). The dosimetric goals were met in 22 patients (79%). There were no Radiation Therapy Oncology Group grade 3+ toxicities; 6 patients (21%) experienced grade 2 events. Most patients (93%) had good/excellent cosmetic outcomes at the last follow-up visit. Conclusions: CT-HDR-IORT is feasible and safe. This promising approach for a conformal, image-based, higher-dose breast IORT is being evaluated in a phase 2 trial.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2020

On numerical errors to the fields surrounding a relativistically moving particle in PIC codes

The particle-in-cell (PIC) method is widely used to model the self-consistent interaction between discrete particles and electromagnetic fields. It has been successfully applied to problems across plasma physics including plasma based acceleration, inertial confinement fusion, magnetically confined fusion, space physics, astrophysics, high energy density plasmas. In many cases the physics involves how relativistic particles (those with high relativistic γ factors) are generated and interact with plasmas. However, when relativistic particles stream across the grid, both in “vacuum” and in plasma, many numerical issues may arise which can lead to unphysical results. We present a detailed analysis of how discretized Maxwell solvers used in PIC codes can lead to numerical errors to the fields that surround particles that move at relativistic speeds across the grid. Expressions for the axial electric field as integrals in k space are presented that reveal two types of errors. The first arises from errors to the numerator of the integrand and leads to unphysical fields that are antisymmetric about the particle. Furthermore, the second arises from errors to the denominator of the integrand and lead to Cherenkov like radiation in “vacuum”. These fields are not anti-symmetric, extend behind the particle, and cause the particle to accelerate or decelerate depending on the solver and parameters. The unphysical fields are studied in detail for two representative solvers - the Yee solver and the FFT based solver. Although the Cherenkov fields are absent, the space charge fields are still present in the fundamental Brillouin zone for the FFT based solvers. In addition, the Cherenkov fields are present in higher order zones for the FFT based solvers. Comparison between the analytical solutions and PIC simulation results are presented. A solution for eliminating these unphysical fields by modifying the k operator in the axial direction is also presented. Using a customized finite difference solver, this solution was successfully implemented into OSIRIS [1]. Results from the customized solver are also presented. Additionally, this solution will be useful for a beam of particles that all move in one direction with a small angular divergence.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Review of in situ process monitoring for metal hybrid directed energy deposition

Hybrid manufacturing, or the combination of additive and subtractive manufacturing within a single build volume is transforming the way products are being fabricated. Additive manufacturing confers unprecedented freedom of design and reduced material usage while enabling serial customization. Subtractive manufacturing provides superior surface finish and improved dimensional accuracies. Interwoven, these two digital manufacturing paradigms are enabling the rapid manufacturing of complex, highly accurate, and customized geometries in a diversity of high-performance alloys. In situ monitoring, heavily relied upon in either additive or subtractive, becomes even more crucial with the interplay of the two processes in a single combined build sequence. Moreover, challenges that do not exist in either process alone can now have a dramatic impact on final part quality: (1) a large amount of heat is generated during additive manufacturing deposition, which is primarily dissipated into the machine tooling and impacts accuracy by deforming the material and causing misaligned machining; (2) microstructure, mechanical properties, and residual stresses are the result of the complex thermal histories generated by additive manufacturing and can impact subsequent cutting performance. This comprehensive review considers previous research in monitoring and providing closed-loop control in both additive and subtractive manufacturing separately and then considers the implications of the effectiveness of these monitoring techniques when additive and subtractive processes are integrated together.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Immobilization and image-guidance methods for radiation therapy of limb extremity soft tissue sarcomas: Results of a multi-institutional survey

Radiation therapy for limb-extremity soft tissue sarcoma (STS) requires accurate, reproducible dose delivery. However, patient positioning is challenging and there is a lack of existing guidelines to assist institutional standardization. Therefore, we conducted a multi-institutional international survey of STS immobilization, image guidance methods, and treatment protocols to investigate current practice. Seventy-three UK radiotherapy centers and 15 hospitals in 7 other countries completed a questionnaire on STS immobilization and image-guidance procedures. Specifically, the survey collated information on the current usage of immobilization equipment, including custom devices, patient setup tolerances, the use of written protocols, the modality and frequency of image guidance, the method of treatment, allocated treatment times, and the application of surgical clips. Multiple combinations of immobilization devices were reported. In the UK, 12%, 40%, 30%, 12%, and 5% use 1, 2, 3, 4, and 5 types of device for lower limb STS. Vacuum bag plus either foot or ankle support was most common (66%). Of 15 international centers, 27%, 60%, 7%, 0%, 7% use 1, 2, 3, 4, 5 devices, with vacuum bags (73%) and thermoplastic (47%) predominant, similar to UK values of 77% and 52%. For image guidance, in the UK, 37% use kV planar, 34% use MV planar, and 16% use cone-beam CT for the first 3 fractions and then weekly. Internationally, daily imaging was more prevalent with 33% using kV planar, 7% MV planar, and 40% cone-beam CT daily. Custom devices plus combinations of devices, along with 5- and 10-mm set-up tolerances, were most commonly reported. Less than half of centers have written treatment protocols. Conventional treatment is most common in the UK, with only 42% using conformal techniques. Treatment is allocated between 10 and 30 minutes. Twenty-six percent of UK centers and 53% of international centers use surgical clips. Across treatment centers, there is no consistent approach to STS immobilization, image-guidance methods, or treatment protocols assessed by this survey. A wide variety of immobilization devices and configurations are utilized, and the frequency and modality of imaging are similarly diverse. In the absence of guidelines, the creation of an online repository of example immobilization techniques could enable centers to compare a diversity of cases. The availability of a forum for viewing and discussing a range of cases could potentially lead to improved patient setup and reduce the time taken to devise an individual immobilization strategy.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2023

Stable electrospray signal on a microfabricated glass chip with three-dimensional open edge and tiered depth geometries

This paper presents the microfabrication and performance of a three-dimensional electrospray ionization (ESI) emitter tip made from glass, which achieves stable current signals important for chemical analysis. Our novel microfabrication process and custom-built signal conditioning hardware provides the advantage of providing accurate features and steady signals. The fabrication process relies on standard microfabrication techniques (i.e., deposition, photolithography, and wet etching). This fabrication method involves the novel application of two layers of positive and negative photoresists in addition to Parafilm® wax tape. Open edge and tiered depth details were successfully created from a multilayer planar mask. This is a benefit for integrated miniaturized and microfluidic systems that often require micro features for their functionality but relatively large millimeter size features for their physical periphery. We demonstrate the fundamental performance of electrospray with this microfluidic chip. The emitter tip was fixed on a linear axis stage with high resolution (10 μm) to finely control the tip distance from a metal counter electrode plate. Further, a custom printed circuit board system was built to safely control four voltages applied to the microchip ports from a single high voltage power supply. To readily form the electrospray, non-aqueous solvents were used for their low viscosity and a constant voltage of +2.7 kV was applied to the sheath electrospray microchannel. The liquid being sprayed was 80/20 (v/v) methanol/acetonitrile with 0.1% acetic acid in the sheath microchannel and with ammonium acetate (10–40 mM) in its remaining microchannels. The electrospray signal was measured in response to varying the distance (1.4 to 1.6mm) between the electrospray emitter tip and a metal counter electrode plate in addition to the varying concentration of the background electrolyte, ammonium acetate. Stable and repeatable electrospray signal showed linear relationships with emitter tip distance and concentration (r 2 ≥ 0.95).

42 ENGINEERING↗