Search NASA⌕ Search

SEARCH · Search NASA

Results for “Key performance indicator”

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 469 records · Page 26

Geothermal Heat Recovery Complex: Large-Scale, Deep Direct-Use System in a Low-Temperature Sedimentary Basin (Final Report)

A feasibility study of using deep direct-use (DDU) geothermal energy to heat agricultural research facilities (ARFs) was conducted at the University of Illinois at Urbana-Champaign (U of IL) and its similar application to military facilities in the Illinois Basin (ILB). The geothermal energy system (GES) investigated utilizes low-temperature (30–90°C; 90–190°F) geothermal fluid (i.e., brine) from an extraction well that is part of a deep, two-well (doublet) system that extends to the bottom of the ILB. The geothermal reservoir modeled, the Mt. Simon Sandstone (MSS), is about 1,280 m (4,200 feet) deep and 457 m thick (1,500 feet) beneath the U of IL. The DDU GES surface infrastructure includes heat exchangers connected in-parallel to pipelines carrying the geothermal fluid and fresh cold and hot water. Analysis of the GES indicated that the MSS can provide a baseload of 2 MMBtu/hr to heat the ARFs by extracting 954 m³/d (6,000 barrels/day [bbl/d]) of geothermal fluid that has a temperature of 44–46 °C (111–115 °F). In addition to analyzing the levelized cost of heat (LCOH) and life cycle costs, the environmental effects of the DDU GES were evaluated, including reduced greenhouse gas (GHG) emissions and water consumption. Multiple system designs were evaluated and then ranked based on their maximum heating performance, energy efficiency, and cost recovery. This feasibility study identified the key components of the fully-integrated DDU technology that can be implemented, both technically and economically. The results and information from this study provides end-users and policy makers with guidance for additional research on the specific components of DDU technology such that its widespread use can provide an uninterruptible energy source, increase resilience from extreme weather conditions, reduce U.S. dependency on fossil fuels, and reduce greenhouse gas (GHG) emissions. The site-specific part of this study gives U of IL administrators a realistic and pragmatic assessment of the financial resources necessary to add a DDU GES in the MSS to the campus’ energy portfolio.

15 GEOTHERMAL ENERGY↗

Divergent Metabolic Changes in Rhizomes of Lowland and Upland Switchgrass (Panicum virgatum) from Early Season through Dormancy Onset

High-biomass-yielding southerly adapted switchgrasses (Panicum virgatum L.) frequently suffer from unpredictable winter hardiness at more northerly sites arising from damage to rhizomes that prevent effective spring regrowth. Previously, changes occurring over the growing season in rhizomes sampled from a cold-adapted tetraploid upland cultivar, Summer, demonstrated a role for abscisic acid (ABA), starch accumulation, and transcriptional reprogramming as drivers of dormancy onset and potential keys to rhizome health during winter dormancy. Here, rhizome metabolism of a high-yielding southerly adapted tetraploid switchgrass cultivar, Kanlow—which is a significant source of genetics for yield improvement—was studied over a growing season at a northern site. Metabolite levels and transcript abundances were combined to develop physiological profiles accompanying greening through the onset of dormancy in Kanlow rhizomes. Next, comparisons of the data to rhizome metabolism occurring in the adapted upland cultivar Summer were performed. These data revealed both similarities as well as numerous differences in rhizome metabolism that were indicative of physiological adaptations unique to each cultivar. Similarities included elevated ABA levels and accumulation of starch in rhizomes during dormancy onset. Notable differences were observed in the accumulation of specific metabolites, the expression of genes encoding transcription factors, and several enzymes linked to primary metabolism.

60 APPLIED LIFE SCIENCES↗

Customized ATP towpreg

Automated tow placement (ATP) utilizes robotic technology to lay down adjacent polymer-matrix-impregnated carbon fiber tows on a tool surface. Consolidation and cure during ATP requires that void elimination and polymer matrix adhesion be accomplished in the short period of heating and pressure rolling that follows towpreg ribbon placement from the robot head to the tool. This study examined the key towpreg ribbon properties and dimensions which play a significant role in ATP. Analysis of the heat transfer process window indicates that adequate heating can be achieved at lay down rates as high as 1 m/sec. While heat transfer did not appear to be the limiting factor, resin flow and fiber movement into tow lap gaps could be. Accordingly, consideration was given to towpreg ribbon having uniform yet non-rectangular cross sections. Dimensional integrity of the towpreg ribbon combined with customized ribbon architecture offer great promise for processing advances in ATP of high performance composites.

Sandusky, Donald A.↗

Brilliant Execution of Smart Labs: Employing Best Practices to Improve Safety and Reduce Energy for Sustainable Labs: Preprint

Laboratory buildings often dominate the energy use on research campuses, consuming three to four times the energy of a typical office building. In most cases, these facilities are defined as “mission critical,” with excessive energy use as simply an unfortunate truth that cannot be avoided without compromising safety. However, case studies indicate cost savings opportunities of up to 40% in laboratories (compared to standard practices) by employing energy efficient design strategies that also improve the safety of lab spaces (Better Buildings 2018). To help stakeholders implement improvement measures, the Smart Labs Toolkit describes a proven approach to optimizing performance of laboratories and critical control environments in new or existing facilities. The Toolkit outlines distinct phases for building a successful Smart Labs program that include: Plan, Assess, Optimize, and Manage. Each phase has specific tasks, training videos, and resources to educate users, support the efforts of key stakeholders, and maximize benefits for the organization in implementing high-performance labs. The Toolkit also includes case studies from the 17 Better Buildings Smart Labs Accelerator partners, sharing lessons learned and supporting the Smart Labs approach to safe, efficient world class science. This paper reviews the technology choices for implementing Smart Labs ventilation strategies, controls, and other efficiency measures. Better Building Smart Lab Accelerator partners provide case study examples of safety and energy-savings results of using Smart Labs approaches.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Performance Data Errors in Air Carrier Operations: Causes and Countermeasures

Several airline accidents have occurred in recent years as the result of erroneous weight or performance data used to calculate V-speeds, flap/trim settings, required runway lengths, and/or required climb gradients. In this report we consider 4 recent studies of performance data error, report our own study of ASRS-reported incidents, and provide countermeasures that can reduce vulnerability to accidents caused by performance data errors. Performance data are generated through a lengthy process involving several employee groups and computer and/or paper-based systems. Although much of the airline indUStry 's concern has focused on errors pilots make in entering FMS data, we determined that errors occur at every stage of the process and that errors by ground personnel are probably at least as frequent and certainly as consequential as errors by pilots. Most of the errors we examined could in principle have been trapped by effective use of existing procedures or technology; however, the fact that they were not trapped anywhere indicates the need for better countermeasures. Existing procedures are often inadequately designed to mesh with the ways humans process information. Because procedures often do not take into account the ways in which information flows in actual flight ops and time pressures and interruptions experienced by pilots and ground personnel, vulnerability to error is greater. Some aspects of NextGen operations may exacerbate this vulnerability. We identify measures to reduce the number of errors and to help catch the errors that occur.

countermeasures↗

Tetratricopeptide Repeat 2 Is a Quantitative Trait Locus That Controls Seed Size

Seed size is a key trait affecting evolution and agronomic performance by influencing seedling establishment in natural populations and crop yields. The Arabidopsis thaliana Seed Size QTL1 (SSQ1) locus explains 10–15% of the variation in seed size. We report here that the causal gene for this locus is Tetratricopeptide Repeat Protein 2 (TPR2), which encodes a co-chaperone. Expressing TPR2 across ecotypes and genotypes showed consistent dosage effects. Each additional TPR2Col-0 allele increased seed mass and volume by 10–14% with high reliability in Col-0, Sha, Tsu-1, and tsu2 genetic backgrounds. Reciprocal genetic crosses indicated that this locus acts maternally, consistent with female sporophytic or female gametophytic mutations. To elucidate how TPR2 regulates seed size, the biomass composition of seeds was measured. While oil content remained unchanged, sucrose levels were markedly elevated in TPR2Col-0 transformant lines and reduced in tpr2 mutants. Interestingly, heterologous expression of TPR2Col-0 across genetic backgrounds increased seed protein accumulation by 18% on average. Based on these changes in sucrose and protein levels, potential modes of action for TPR2 are discussed.

Biochemistry & Molecular Biology↗

Developing Glassy Magnets from Simulated Composition of Martian Soil for Exploration Applications

The long-term exploration goals of NASA include developing human habitation on Mars and conducting scientific investigations on Mars and other planetary bodies. In situ resource processing is a key objective in this area We focus OR the possibility of making magnetic glasses in situ for potential applications development. The paper will focus on ongoing work at NASA Marshall Space Flight Center on making magnetic glass h m Mars soil simulants and its characterization. Analysis of the glass morphology, strength, chemistry and resulting magnetic properties will provide a fi.mdamenta1 understanding ofthe synthesized materiai that can be used for pomtiai appiications cieveiopment. In an effort to characterize the magnetic properbes of the Mars glasses, a series of tests were performed at NASA MSFC. Preliminary tests indicated that the glasses were attracted to a magnet and also had a small amount of residual magnetism. They were opaque (almost black in color). As the first step, a sample of Mars 1 glass (-lm x lmm x 5 mm length) was machined, weighed and its hysteresis curve was measured using a Vibration Sample Magnetometer 0. Next, a small furnace was designed and built and the sample was baked in a graphite (reducing agent) crucible at 800 C in an Argon atmosphere for 3 hours in the presence of a uniform, transverse (transverse to the 5mm length of the sample) magnetic field of 0.37 Tesla. The treated sample showed reddening on the outside and showed substantially increased residual magnetism. This sample was again analyzed in the VSM. The data clearly showed that some chemical change occurred during the heat treatment (color change) and that both the glasses have useful magnetic properties. Although no orientation effects of the magnetic field were considered, the data showed the following: 1. Both glass samples are primarily soft magnets and display ferromagnetic behavior (hysteresis, saturation, etc.) 2. The treated glass has improved saturation magnetism (order of magnitude increase), retentivity (factor of 6 increase) and susceptibility (order of magnitude increase) compared to the untreated glass 3. The untreated sample has higher coercivity (-50% that of Nickel) than the treated sample

Ramachandran, Narayanan↗

Developing Glassy Magnets from Simulated Composition of Martian Soil for Exploration Applications

The long-term exploration goals of NASA include developing human habitation on Mars and conducting scientific investigations on Mars and other planetary bodies. In situ resource processing is a key objective in this area. We focus on the possibility of making magnetic glasses in situ for potential applications development. The paper will focus on ongoing work at NASA Marshall Space Flight Center on making magnetic glass from Mars soil simulants and its characterization. Analysis of the glass morphology, strength, chemistry and resulting magnetic properties will provide a fundamental understanding of the synthesized material that can be used for potential applications development. in an effort to characterize the magnetic properties of the Mars glasses, a series of tests were performed at NASA MSFC. Preliminary tests indicated that the glasses were attracted to a magnet and also had a small amount of residual magnetism. They were opaque (almost black in color). As the first step, a sample of Mars 1 glass (approx.1 mm x 1 mm x 5 mm length) was machined, weighed and its hysteresis curve was measured using a Vibration Sample Magnetometer (VSM). Next, a small furnace was designed and built and the sample was baked in a graphite (reducing agent) crucible at 800 C in an Argon atmosphere for 3 hours in the presence of a uniform, transverse (transverse to the 5mm length of the sample) magnetic field of 0.37 Tesla. The treated sample showed reddening on the outside and showed substantially increased residual magnetism. This sample was again analyzed in the VSM. The data clearly showed that some chemical change occurred during the heat treatment (color change) and that both the glasses have useful magnetic properties. Although no orientation effects of the magnetic field were considered, the data showed the following: 1. Both glass samples are primarily soft magnets and display ferromagnetic behavior (hysteresis, saturation, etc.) 2. The treated glass has improved saturation magnetism (order of magnitude increase), retentivity (factor of 6 increase) and susceptibility (order of magnitude increase) compared to the untreated glass 3. The untreated sample has higher coercivity (approx.50% that of Nickel) than the treated sample 4. Both samples have similar energy density. Results from a systematic study to quantify the effects of processing conditions such as heat treatment, atmosphere, containerless processing (by electrostatic levitation), and applications of external magnetic fields of different strengths will be discussed. Efforts on optimizing the magnetic properties of the product and the feasibility of using it for a couple of specific magnetic applications such as heat generation using an ac field and for electro forming will also be covered. The latter is an in situ manufacturing technique being studied for in-space fabrication applications at MSFC.

Ramachandran, N.↗

Acidity-Governed Rules in the Electrochemical Performance of Fluorinated Benzenes for High-Voltage Lithium Metal Batteries

Judicious selection of the optimal fluorobenzene (FB) as a nonsolvating cosolvent for lithium metal batteries (LMBs) is reported. For this work, we found the key correlation between FB structures and cycling stabilities of cells: increased fluorine substitution of FBs results in higher anodic stability but at the expense of reduced reductive stability, and FBs containing three or more fluorine atoms exhibit insufficient anodic stability in the electrolyte system comprised of fluoroethylene carbonate (FEC) and ethyl methyl carbonate (EMC). More importantly, FBs with higher acidity (lower pK a ) due to protons located between two adjacent fluorine atoms tend to be more susceptible to side reactions during cycling. Our results indicate that difluorobenzenes with no “acidic” proton (DFB2 and DFB4) have emerged as the optimal choice with the desired redox stability in high-voltage LMBs. Nuclear magnetic resonance and X-ray photoelectron spectroscopy confirmed these findings, providing guidance for selecting the most suitable FB variants as nonsolvating cosolvents for high-voltage LMBs.

25 ENERGY STORAGE↗

Numerical studies of collinear laser-assisted injection from a foil for plasma wakefield accelerators

We present a laser-assisted electron injection scheme for beam-driven plasma wakefield acceleration. The laser is collinear with the driver and triggers the injection of hot electrons into the plasma wake by interaction with a thin solid target. We present a baseline case using the AWAKE Run 2 parameters and then perform variations on key parameters to explore the scheme. It is found that the trapped witness electron charge may be tuned by altering laser parameters, with a strong dependence on the phase of the wake upon injection. Normalized emittance settles at the order of micrometres and varies with witness charge. The scheme is robust to misalignment, with a 1/10th plasma skin-depth offset ( 20 μ m for the AWAKE case) having a negligible effect on the final beam. The final beam quality is better than similar existing schemes, and several avenues for further optimization are indicated. The constraints on the AWAKE experiment are very specific, but the general principles of this mechanism can be applied to future beam-driven plasma wakefield accelerator experiments. Published by the American Physical Society 2024

Physics↗

Agentic AI vs ML-Based Autotuning: A Comparative Study for Loop Reordering Optimization

High Performance Computing (HPC) applications rely heavily on code optimizations to achieve good performance on modern CPU and GPU architectures. Traditional Machine Learning auto-tuning approaches have demonstrated success in exploring high-dimensional spaces, but they often require expensive compile-run evaluations and lack adaptability for large HPC applications. The recent advances in Large Language Models (LLMs) and Agentic AI systems raise intriguing questions about the potential of these approaches to address specific optimization methodologies. This work aims to answer an essential question for the HPC community: “How Agentic AI Systems Compare to Traditional ML Autotuning Techniques?” To address this question, we present a comparative analysis between a traditional ML-based optimization approach and an Agentic AI system, evaluating their respective capabilities and limitations for loop-level optimization. In addition, we introduced a new Agentic AI system named LoopGen-AI using three different Large Language Models: GPT-4.1, Claude 4.0, and Gemini 2.5. A key finding is that LoopGen-AI achieves competitive per-formance with only a few program runs, the reasoning logs from the agents revealed that their decisions rely heavily on the combination of semantic understanding of the target kernel with dynamic feedback from the environment, highlighting a promising new dimension in performance tuning. In contrast, ML-based autotuners focus on statistical exploration, and require orders of magnitude more runs to reach peak performance. Additionally, our analysis shows that prompt engineering, particularly using Persona + Context Manager patterns, significantly impacts the effectiveness of Agentic AI. Our results indicate that while Agentic AI systems are not yet a complete replacement for ML-based autotuners, it can effectively complement traditional methods.

Rosas, Miguel Romero↗

Measurements of low-mode asymmetries in the areal density of laser-direct-drive deuterium–tritium cryogenic implosions on OMEGA using neutron spectroscopy

Areal density is one of the key parameters that determines the confinement time in inertial confinement fusion experiments, and low-mode asymmetries in the compressed fuel are detrimental to the implosion performance. The energy spectra from the scattering of the primary deuterium–tritium (DT) neutrons off the compressed cold fuel assembly are used to investigate low-mode nonuniformities in direct-drive cryogenic DT implosions at the Omega Laser Facility. For spherically symmetric implosions, the shape of the energy spectrum is primarily determined by the elastic and inelastic scattering cross sections for both neutron-deuterium and neutron-tritium kinematic interactions. Two highly collimated lines of sight, which are positioned at nearly orthogonal locations around the OMEGA target chamber, record the neutron time-of-flight signal in the current mode. An evolutionary algorithm is being used to extract a model-independent energy spectrum of the scattered neutrons from the experimental neutron time-of-flight data and is used to infer the modal spatial variations (l = 1) in the areal density. Experimental observations of the low-mode variations of the cold-fuel assembly (ρL 0 + ρL 1 ) show good agreement with a recently developed model, indicating a departure from the spherical symmetry of the compressed DT fuel assembly. As a result, another key signature that has been observed in the presence of a low-mode variation is the broadening of the kinematic end-point due to the anisotropy of the dense fuel conditions.

47 OTHER INSTRUMENTATION↗

Toward a high-voltage fast-charging pouch cell with TiO 2 cathode coating and enhanced battery safety

Nickel-rich layered lithium transition metal oxides, LiNi x Co y Mn 1-x-y O 2 , are key cathode materials for high-energy lithium-ion batteries owing to their high specific capacity. However, the commercial deployment of nickel-rich oxides has been hampered by their poor thermostability and insufficient cycle life. In this work full batteries with uncoated and TiO 2 -coated LiNi 0.5 Co 0.2 Mn 0.3 O 2 cathodes and graphite anodes are compared in terms of electrochemical performance and safety behavior. The battery using a TiO 2 -coated LiNi 0.5 Co 0.2 Mn 0.3 O 2 cathode exhibited better cyclic performance at high cutoff voltage. Electrochemical impedance spectroscopy analysis indicated that the TiO 2 -coated LiNi 0.5 Co 0.2 Mn 0.3 O 2 cathode gave the battery a more stable charge transfer resistance. Transmission electron microscopy demonstrated that TiO 2 coating reduced accumulation of the cathode electrolyte interface layer on the particle surface. Time-of-flight secondary ion mass spectrometry demonstrated that TiO 2 coating markedly enhanced the interface stability of the cathode particle and protected the particle from serious etching by the electrolyte. Accelerating rate calorimetry revealed that the trigger temperature of thermal runaway for the battery using TiO 2 -coated LiNi 0.5 Co 0.2 Mn 0.3 O 2 as cathode material was 257 °C, which was higher than that of the battery with the uncoated LiNi 0.5 Co 0.2 Mn 0.3 O 2 cathode (251 °C). In situ X-ray diffraction during heating demonstrated that this enhanced safety can be attributed to the suppressed phase evolution of the coated cathode material.

25 ENERGY STORAGE↗

Gamma radiation sterilization of N95 respirators leads to decreased respirator performance

In response to personal protective equipment (PPE) shortages in the United States due to the Coronavirus Disease 2019, two models of N95 respirators were evaluated for reuse after gamma radiation sterilization. Gamma sterilization is attractive for PPE reuse because it can sterilize large quantities of material through hermetically sealed packaging, providing safety and logistic benefits. The Gamma Irradiation Facility at Sandia National Laboratories was used to irradiate N95 filtering facepiece respirators to a sterilization dose of 25 kGy(tissue). Aerosol particle filtration performance testing and electrostatic field measurements were used to determine the efficacy of the respirators after irradiation. Both respirator models exhibited statistically significant decreases in particle filtering efficiencies and electrostatic potential after irradiation. The largest decrease in capture efficiency was 40–50% and peaked near the 200 nm particle size. The key contribution of this effort is correlating the electrostatic potential change of individual filtration layer of the respirator with the decrease filtration efficiency after irradiation. This observation occurred in both variations of N95 respirator that we tested. Electrostatic potential measurement of the filtration layer is a key indicator for predicting filtration efficiency loss.

36 MATERIALS SCIENCE↗

Chemical kinetic analysis of hydrogen-air ignition and reaction times

An anaytical study of hydrogen air kinetics was performed. Calculations were made over a range of pressure from 0.2 to 4.0 atm, temperatures from 850 to 2000 K, and mixture equivalence ratios from 0.2 to 2.0. The finite rate chemistry model included 60 reactions in 20 species of the H2-O2-N2 system. The calculations also included an assessment of how small amounts of the chemicals H2O, NOx, H2O2, and O3 in the initial mixture affect ignition and reaction times, and how the variation of the third body efficiency of H2O relative of N2 in certain key reactions may affect reaction time. The results indicate that for mixture equivalence ratios between 0.5 and 1.7, ignition times are nearly constant; however, the presence of H2O and NO can have significant effects on ignition times, depending on the mixture temperature. Reaction time is dominantly influenced by pressure but is nearly independent of initial temperature, equivalence ratio, and the addition of chemicals. Effects of kinetics on reaction at supersonic combustor conditions are discussed.

Rogers, R. C.↗

Deformation and Life Analysis of Composite Flywheel Disk and Multi-disk Systems

In this study an attempt is made to put into perspective the problem of a rotating disk, be it a single disk or a number of concentric disks forming a unit. An analytical model capable of performing an elastic stress analysis for single/multiple, annular/solid, anisotropic/isotropic disk systems, subjected to both pressure surface tractions, body forces (in the form of temperature-changes and rotation fields) and interfacial misfits is derived and discussed. Results of an extensive parametric study are presented to clearly define the key design variables and their associated influence. In general the important parameters were identified as misfit, mean radius, thickness, material property and/or load gradation, and speed; all of which must be simultaneously optimized to achieve the "best" and most reliable design. Also, the important issue of defining proper performance/merit indices (based on the specific stored energy), in the presence of multiaxiality and material anisotropy is addressed. These merit indices are then utilized to discuss the difference between flywheels made from PMC and TMC materials with either an annular or solid geometry. Finally two major aspects of failure analysis, that is the static and cyclic limit (burst) speeds are addressed. In the case of static limit loads, upper, lower, and out-of-plane bounds for disks with constant thickness are presented for both the case of internal pressure loading (as one would see in a hydroburst test) and pure rotation (as in the case of a free spinning disk). The results (interaction diagrams) are displayed graphically in designer friendly format. For the case of fatigue, a representative fatigue/life master curve is illustrated in which the normalized limit speed versus number of applied cycles is given for a cladded TMC disk application.

Arnold, S. M.↗

Laser powder bed fusion parameter estimation with k-NN

Abstract Laser powder bed fusion (L-PBF) is a technique within additive manufacturing that uses a high power density laser to build parts from fused powdered metal alloy. This technology is well equipped to produce complex parts with otherwise impossible features, such as hidden voids or lattice structures. Alongside capability, reliability and quality are key characteristics considered when choosing a manufacturing method, and these are gaining attention as this method becomes more prevalent in industry. One main indicator of a stable L-PBF process is consistent melt pool geometry, and the properties of which are likely to determine the quality of the part produced. As computing power and sensing technologies become more advanced, this melt pool geometry could be studied in real time. This work addresses the challenge by leveraging a k-nearest neighbor (k-NN) model to identify key features within melt pool imagery and predict the energy density. The k-NN model was trained on data provided by the National Institute of Standards and Technology (NIST). Data preprocessing was performed on the images to extract features that were used in the k-NN model. This approach was used to accurately infer the energy density of unseen layers within the same part. The algorithm was subsequently tested with unique scan strategies and found to reasonably estimate the energy density of different parts. A fivefold cross validation found the algorithm to be consistently predicting the class of 91.4% of the in situ melt pool images.

Jung, Patrick (ORCID:0000000267890859)↗

Sequential Selection for Minimizing the Variance with Application to Crystallization Experiments

For many crystal-based products (e.g., pharmaceuticals, energy storage), the size uniformity is not only a key quality attribute, but sometimes also an indicator of other attributes such as solid purity. This article proposes a sequential selection approach to find a proper experimental setting that leads to high uniformity, or equivalently, small variance for crystal sizes, from the advanced slug flow reaction crystallization process of a model crystal, called manganese oxalate hydrate. The proposed sequential selection approach contains a Bayesian adaptive method to incorporate new uniformity measurements in each step and two design acquisition functions to improve the selection of the most promising experimental setting in terms of minimizing the variance. We study the performance of the proposed approach through multiple synthetic numerical studies, as well as a case study based on data from slug flow crystallization experiments. Throughout these studies, the proposed approach shows competitive performance in identifying the best experimental setting.

Expected improvement↗