Search NASA⌕ Search

SEARCH · Search NASA

Results for “shape optimization”

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 1,189 records · Page 66
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

X-ray methods to observe and quantify adhesive penetration into wood

To accelerate the development of new and improved wood adhesives for engineered wood products, the optimal penetration of adhesives into wood needs to be determined. Adhesive penetration includes both the flow of adhesives into wood micron-scale voids and the infiltration into the polymer components of the wood cell wall layers. In this work, X-ray computed tomography (XCT) and X-ray fluorescence microscopy (XFM) were used to study adhesive flow and infiltration. Model wood-adhesive bondlines were made using loblolly pine ( Pinus taeda ) latewood substrates and bromine-substituted phenol formaldehyde (BrPF) resins with different weight average molecular weight (M W ). The Br substitution facilitated both qualitative and quantitative observations using XCT and XFM. The BrPF resin flow into wood was visualized using XCT volume reconstructions and quantified by calculating the weighted penetration (WP). Examination of the shape of the cured BrPF-air interface in longitudinal tracheid lumina revealed that capillary played a role in the majority of BrPF flow into lumina. XFM mapping revealed the pathways of BrPF infiltration into the wood cell walls, and the results were used to calculate BrPF cell wall weight percent gain (WPG CW ) in individual wood cell wall layers. Both WP and WPG CW decreased with increasing BrPF M W . Also, the middle lamella had higher WPG CW than its neighboring secondary cell walls, and within a given bondline the WPG CW decreased with increasing distance of the cell from the bondline. Along these lines, the results provide new insights that are needed in the development of improved models to understand and predict wood adhesive bondline performance.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Artificial intelligence inferred microstructural properties from voltage–capacity curves

Abstract The quantification of microstructural properties to optimize battery design and performance, to maintain product quality, or to track the degradation of LIBs remains expensive and slow when performed through currently used characterization approaches. In this paper, a convolution neural network-based deep learning approach (CNN) is reported to infer electrode microstructural properties from the inexpensive, easy to measure cell voltage versus capacity data. The developed framework combines two CNN models to balance the bias and variance of the overall predictions. As an example application, the method was demonstrated against porous electrode theory-generated voltage versus capacity plots. For the graphite|LiMn $$_2$$ 2 O $$_4$$ 4 chemistry, each voltage curve was parameterized as a function of the cathode microstructure tortuosity and area density, delivering CNN predictions of Bruggeman’s exponent and shape factor with 0.97 $$R^2$$ R 2 score within 2 s each, enabling to distinguish between different types of particle morphologies, anisotropies, and particle alignments. The developed neural network model can readily accelerate the processing-properties-performance and degradation characteristics of the existing and emerging LIB chemistries.

25 ENERGY STORAGE↗
DOE OSTI2024

Assessment of vertical stability for negative triangularity pilot plants

Abstract Negative triangularity (NT) tokamak configurations may be more susceptible to magneto-hydrodynamic instability, posing challenges for recent reactor designs centered around their favorable properties, such as improved confinement and operation free of edge-localized modes. In this work, we assess the vertical stability of plasmas with NT shaping and develop potential reactor solutions. When coupled with a conformal wall, NT equilibria are confirmed to be less vertically stable than equivalent positive triangularity (PT) configurations. Unlike PT, their vertical stability is degraded at higher poloidal beta. Furthermore, improvements in vertical stability at low aspect ratio do not translate to the NT geometry. NT equilibria are stabilized in PT vacuum vessels due to the increased proximity of the plasma and the wall on the outboard side, but this scenario is found to be undesirable due to reduced vertical gaps which give less spatial margin for control recovery. Instead, we demonstrate that informed positioning of passively conducting plates can lead to improved vertical stability in NT configurations on par with stability metrics expected in PT scenarios. An optimal setup for passive plates in highly elongated NT devices is presented, where plates on the outboard side of the device reduce vertical instability growth rates to 16% of their baseline value. For lower target elongations, integration of passive stabilizers with divertor concepts can lead to significant improvements in vertical stability. Plates on the inboard side of the device are also uniquely enabled in NT geometries, providing opportunity for spatial separation of vertical stability coils and passive stabilizers.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Tandem neural network-based controller for x-ray bimorph mirrors

Nanometer-scale shape control of x-ray mirrors is crucial for coherent x-ray beam experiments at low-emittance synchrotron beamline instruments. Piezoelectric bimorph mirrors offer adaptive control but are hindered by nonlinearities such as cross talk, creep, and hysteresis. To overcome these limitations, we present a novel feedback-free control solution, inspired by the proportional–integral–derivative (PID) scheme, driven by tandem neural networks (TNNs). Using task-specific datasets, the TNN-based system predicts actuator voltages with greater speed, accuracy, and stability than a single NN-based model. This approach is ideal for real-time applications, such as adapting beam focus to dynamic sample sizes while maintaining precise wavefront quality. Our findings highlight the potential of artificial intelligence in rapidly optimizing adaptive optics and managing nonlinear control systems.

Zhang, Runyu↗
DOE OSTI2024

The ORNL Moderator Test Station Science Case

Oak Ridge National Laboratory (ORNL) hosts two world-leading slow neutron sources, the Spallation Neutron Source (SNS) and the High Flux Isotope Reactor (HFIR), and is currently developing the technical design for a Second Target Station (STS) for the SNS. Upon completion of the STS project, ORNL will be uniquely positioned to optimize each of its three neutron sources, the SNS First Target Station (FTS), the STS, and HFIR, in a complementary way. Among the essential aspects of a re-imagined FTS and the current STS design are high-brightness parahydrogen moderators—moderators which are optimized for high per-unit-area neutron brightness rather than integrated-across-large-area neutron intensity. The high-brightness moderators proposed for the STS will, for the brightness metric, significantly outperform the coupled moderators currently on the FTS for appropriately optimized neutron beamlines, provided the moderating hydrogen is converted to near-equilibrium levels of parahydrogen (approximately 99.8% at 20 K). The original FTS moderators, by contrast, were conservatively designed to be relatively insensitive to the exact ortho:para ratio, with a consequent loss in performance. As a result, a redesign of the FTS moderators assuming fully converted parahydrogen could result in significant performance improvements on the FTS coupled moderators, and more consistent performance over time for all hydrogen moderators. This “parahydrogen problem” is a long-standing challenge for the effective implementation of hydrogen cold moderators at high-power neutron sources. In addition, the development of new moderator concepts, whether based on previously unused materials, structured heterogeneous arrays, or even simply on changes in overall shape and size is significantly restricted at a large-scale production facility intended to use the resulting neutron beams. Accordingly, moderators for production neutron sources are often designed in a very conservative, low-risk fashion, even though this compromises the absolute neutronic performance. Advanced moderator concepts worthy of study include features that could not be tested without redesigning and redeploying the entire existing reflector, shielding, and neutron beamline installation, making such development efforts far more expensive than building a stand-alone test facility.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2020

A Moderator Test Station at ORNL

Oak Ridge National Laboratory (ORNL) hosts two world-leading slow neutron sources, the Spallation Neutron Source (SNS) and the High Flux Isotope Reactor (HFIR), and is currently developing the technical design for a Second Target Station (STS) for the SNS. Upon completion of the STS project, ORNL will be uniquely positioned to optimize each of its three neutron sources, the SNS First Target Station (FTS), the STS, and HFIR, in a complementary way. Among the essential aspects of a reimagined FTS and the current STS concept are high-brightness parahydrogen moderators—moderators which are optimized for high per-unit-area neutron brightness rather than integrated-across-large-area neutron intensity. The high-brightness moderators proposed for the STS will significantly outperform the coupled moderators currently on the FTS for appropriately optimized neutron beamlines, provided the moderating hydrogen is converted to near-equilibrium levels of parahydrogen (approximately 99.8% at 20 K). The original FTS moderators, by contrast, were conservatively designed to be relatively insensitive to the exact ortho:para ratio, with a consequent loss in performance. As a result, a redesign of the FTS moderators assuming fully converted parahydrogen could result in significant performance improvements on the FTS coupled moderators, and more consistent performance over time for all hydrogen moderators. This “parahydrogen problem” is a long-standing challenge for the effective implementation of hydrogen cold moderators at high-power neutron sources. In addition, the development of new moderator concepts, whether based on previously unused materials, structured heterogeneous arrays, or even simply on changes in overall shape and size is significantly restricted at a large-scale production facility intended to use the neutron beams so produced. Accordingly, moderators for production neutron sources are often designed in a very conservative, low-risk fashion, even though this compromises the absolute neutronic performance. Advanced moderator concepts worthy of study include features that could not be tested without redesigning and redeploying the entire existing reflector, shielding, and neutron beamline installation, making such development efforts far more expensive than building a stand-alone test facility. We propose a Moderator Test Station (MTS) at the SNS with which we will verify such performance gains and test new moderator concepts. These concepts include both high-brightness and large-volume parahydrogen moderators, as well as moderators with tailored ortho:para hydrogen levels, heterogeneous moderator concepts such as the convoluted moderator or pelletized moderators, and moderators made of materials like ammonia, ethane, and oxygen clathrates, which have not been widely tested let alone deployed at neutron source facilities.

42 ENGINEERING↗
DOE OSTI2017

“Roller-Wheel”-Type Pt-Containing Small Molecules and the Impact of “Rollers” on Material Crystallinity, Electronic Properties, and Solar Cell Performance

We report the synthesis, characterization, and detailed comparison of a series of novel Pt-bisacetylide containing conjugated small molecules possessing an unconventional “roller-wheel” shaped structure that is distinctly different from the “dumbbell” designs in traditional Pt-bisacetylide containing conjugated polymers and small molecules. The relationships between the chemical nature and length of the “rollers” and the electronic and physical properties of the materials are carefully studied by steady-state spectroscopy, cyclic voltammetry, differential scanning calorimetry, single-crystal X-ray diffraction, transient absorption spectroscopy, theoretical calculation, and device application. It was revealed that if the roller are long enough, these molecules can “slip-stack” in the solid state, leading to high crystallinity and charge mobility. Organic solar cells were fabricated and showed power conversion efficiencies up to 5.9%, out-performing all existing Pt-containing materials. The device performance was also found to be sensitive to optimization conditions and blend morphologies, which are a result of the intricate interplay among materials crystallinity, phase separation, and the relative positions of the lowest singlet and triplet excited states.

36 MATERIALS SCIENCE↗
DOE OSTI2020

HPC4Mfg with Samsung: Making semiconductor devices cool through HPC ab initio simulations

For decades, the semiconductor technology has followed the Moore’s law, making newer devices more powerful and energy efficient. Recently, however, it has reached a point where the performance and the energy efficiency of the device do not improve with the shrinking device size. One of the fundamental reasons of this deviation from the past trend is the interconnect resistance, which becomes larger with the shrinking size. The devices size is so small that the quantum mechanical effects can no longer be ignored and the traditional continuum simulation tools such as TCAD become inadequate. In this project, Samsung Semiconductor Inc. and Lawrence Berkeley National Laboratory has collaborated to perform first of kind device-scale ab initio simulations to optimize materials and interconnect morphology to minimize interconnect resistance. We have tested the use of LS3DF method and the PEtot_trans approach on top of the folded spectrum method (FSM) Escan code to calculate the scattering state, and to study various effects influence the interconnect conductivity. We found that, the LS3DF can be used to calculate such metallic system. On the other hand, the use of Escan code to solve the linear equation is not practical due to the slow convergence. We have implemented a Chebyshev filter technique to calculate a few hundred eigen states near the scattering state energy E, then use these eigen states as preconditioner to solve the linear equation. We have used this approach to study the different factors which affect the interconnect conductivity, including the shape, the point defect, the temperature, and the grain boundary.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Seismic Performance of Conventional and Additively Manufactured U-Shaped Flexural Plates

U-shape flexural plates (UFPs) have gained significant attention in seismic structural design due to their ability to provide stable hysteresis behaviour and serve as effective energy-dissipating devices. Concurrently, Additive Manufacturing (AM) has advanced significantly, enabling the production of metallic components with mechanical properties comparable to those of conventionally manufactured cold-rolled materials. This study aims to explore the seismic response of single and double UFP fabricated through Laser Powder Based Fusion (LPBF) and conventional cold rolled 316L stainless steel (SS). The experimental results are evaluated based on force-displacement hysteresis behaviour, energy dissipation capacity, load-carrying capacity, and stiffness degradation. The findings confirm the efficacy of AM-fabricated UFPs for seismic energy dissipation. Additionally, the results suggest the potential for further improvement through the optimization of AM process parameters, such as laser scan speed, hatch spacing, and layer thickness, to enhance hysteretic performance and energy dissipation characteristics.

Risal, Kshitiz [Idaho State University]↗
DOE OSTI2024

Unsupervised learning-enabled pulsed infrared thermographic microscopy of subsurface defects in stainless steel

Metallic structures produced with laser powder bed fusion (LPBF) additive manufacturing method (AM) frequently contain microscopic porosity defects, with typical approximate size distribution from one to 100 microns. Presence of such defects could lead to premature failure of the structure. In principle, structural integrity assessment of LPBF metals can be accomplished with nondestructive evaluation (NDE). Pulsed infrared thermography (PIT) is a non-contact, one-sided NDE method that allows for imaging of internal defects in arbitrary size and shape metallic structures using heat transfer. PIT imaging is performed using compact instrumentation consisting of a flash lamp for deposition of a heat pulse, and a fast frame infrared (IR) camera for measuring surface temperature transients. However, limitations of imaging resolution with PIT include blurring due to heat diffusion, sensitivity limit of the IR camera. We demonstrate enhancement of PIT imaging capability with unsupervised learning (UL), which enables PIT microscopy of subsurface defects in high strength corrosion resistant stainless steel 316 alloy. PIT images were processed with UL spatial–temporal separation-based clustering segmentation (STSCS) algorithm, refined by morphology image processing methods to enhance visibility of defects. The STSCS algorithm starts with wavelet decomposition to spatially de-noise thermograms, followed by UL principal component analysis (PCA), fine-tuning optimization, and neural learning-based independent component analysis (ICA) algorithms to temporally compress de-noised thermograms. The compressed thermograms were further processed with UL-based graph thresholding K-means clustering algorithm for defects segmentation. The STSCS algorithm also includes online learning feature for efficient re-training of the model with new data. For this study, metallic specimens with calibrated microscopic flat bottom hole defects, with diameters in the range from 203 to 76 µm, were produced using electro discharge machining (EDM) drilling. While the raw thermograms do not show any material defects, using STSCS algorithm to process PIT images reveals defects as small as 101 µm in diameter. To the best of our knowledge, this is the smallest reported size of a sub-surface defect in a metal imaged with PIT, which demonstrates the PIT capability of detecting defects in the size range relevant to quality control requirements of LPBF-printed high-strength metals.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Direct current magnetic Hall probe technique for measurement of field penetration in thin film superconductors for superconducting radio frequency resonators

Superconducting Radio Frequency (SRF) cavities used in particle accelerators are typically formed from or coated with superconducting materials. Currently, high purity niobium is the material of choice for SRF cavities that have been optimized to operate near their theoretical field limits. This brings about the need for significant R & D efforts to develop next generation superconducting materials that could outperform Nb and keep up with the demands of new accelerator facilities. To achieve high quality factors and accelerating gradients, the cavity material should be able to remain in the superconducting Meissner state under a high RF magnetic field without penetration of quantized magnetic vortices through the cavity wall. Therefore, the magnetic field at which vortices penetrate a superconductor is one of the key parameters of merit of SRF cavities. Techniques to measure the onset of magnetic field penetration on thin film samples need to be developed to mitigate the issues with the conventional magnetometry measurements that are strongly influenced by the film orientation and shape and edge effects. In this work, we report the development of an experimental setup to measure the field of full flux penetration through films and multi-layered superconductors. Our system combines a small superconducting solenoid that can generate a magnetic field of up to 500 mT at the sample surface and three Hall probes to detect the full flux penetration through the superconductor. We report this setup can be used to study alternative materials that could potentially outperform niobium, as well as superconductor–insulator–superconductor (SIS) multilayer coatings on niobium.

47 OTHER INSTRUMENTATION↗
DOE OSTI2019

Tunable Porosity in Fused Filament 3D-Printed Blends of Intrinsically Porous Polymer and Thermoplastic Aliphatic Polyesters Polycaprolactone and Polylactic Acid

Future advances and usage of all-organic polymeric materials with permanent void spaces and high surface areas, in applications such as separations or as supports, depends heavily on the development of processing techniques to produce complex geometry objects. Here, the high free volume glassy microporous polymer PIM-1 was fabricated, as a major component in a polymer blend, into complex and customizable 3D objects by fused filament fabrication (FFF). PIM-1 was found to be compatible with polycaprolactone (PCL) and polylactic acid (PLA) and thus could be processed by extrusion into filaments with high loadings of PIM-1 (50% by mass). Ternary PCL/PLA/PIM-1 composite filaments provided an optimal balance of durability and melt flow characteristics for consistent FFF 3D printing of intricate structures. As printed, the micropores of PIM-1 were blocked and inaccessible to N2 during sorption experiments; however, the ternary composite structures displayed significant meso- and macroporosity and nanostructured phase separation. Postprinting immersion in 3-chloro-1-propanol was identified to selectively remove PCL within the composites, re-expose the characteristic micropores of PIM-1, and retain the macrostructure of the printed object. After postprinting treatments, specific surface areas by the Brunauer–Emmett–Teller method (as high as 460 m2 g–1) were found to directly correlate with the PCL content originally present. In conclusion, the extrusion-based processing methodology provides a new approach for production of intrinsically porous polymer objects in custom and complex shapes by reinforcement with thermoplastics (PCL and PLA).

36 MATERIALS SCIENCE↗
DOE OSTI2023

Measurements of Magnetic Field Penetration of Materials for Superconducting Radiofrequency Cavities

Superconducting Radio Frequency (SRF) cavities used in particle accelerators are typically formed from or coated with superconducting materials. Currently high purity niobium is the material of choice for SRF cavities which have been optimized to operate near their theoretical field limits. This brings about the need for significant R&D efforts to develop next generation superconducting materials which could outperform Nb and keep up with the demands of new accelerator facilities. To achieve high quality factors and accelerating gradients, the cavity material should be able to remain in the superconducting Meissner state under high RF magnetic field without penetration of quantized magnetic vortices through the cavity wall. Therefore, the magnetic field at which vortices penetrate in a supercon- ductor is one of the key parameters of merit of SRF cavities. Techniques to measure the onset of magnetic field penetration on thin film samples need to be developed to mitigate the issues with the conventional magnetometry measurements which are strongly influenced by the film orientation and shape and edge effects. The applied magnetic field is also needed to be parallel to the one side of the superconductor to resemble the magnetic field profile at the surface of the SRF cavities operating at fundamental accelerating mode. In this work we report the development of an experimental setup called Magnetic Field Penetration (MFP) magnetometer to measure the field of full flux penetration through bulk, thin films and multilayered superconductors. Our system combines a small superconducting solenoid which can generate the magnetic field up to 500 mT at the sample surface and three Hall probes to detect the full flux penetration through the planner superconductor with 2 inch diameter. This setup was used to study alternative materials which could potentially outperform niobium, as well as SIS multilayer coatings on niobium.

Senevirathne, Iresha↗
DOE OSTI2022

Nucleon-pair truncation of the shell model for medium-heavy nuclei

Background: Establishing computationally tractable models of atomic nuclei is a long-time goal of nuclear structure physics. A flexible framework which easily includes excited states and many-body correlations is the configuration-interaction shell model (SM), but the exponential growth of the basis means one needs an efficient truncation scheme, ideally one that includes both deformation and pairing correlations. Purpose: Here, we propose an efficient truncation scheme of the SM: starting from a pair condensate variationally defined by Hartree-Fock single-particle states and the particle-number conserved Bardeen-Cooper-Schrieffer (NBCS) approximation, we carry out projection of states with good angular momentum. Methods: After generating Hartree-Fock single-particle states with Kramers degeneracy in a SM space, we optimize the pair amplitudes in the NBCS by minimizing the energy, and then use linear algebra projection (LAP) of states with good angular momentum. Both NBCS and LAP are computationally fast. Results: Our calculations yield good agreement with full configuration-interaction SM calculations for low-lying states of transitional and rotational nuclei with axially symmetric and triaxial deformation in medium- and heavy-mass regions: 44,46,48 Ti, 48,50 Cr, 52 Fe, 60,62,64 Zn, 66,68 Ge, 68 Se, and 108,110 Xe. We predict low-lying states of 112–114 Ba and 116–120 Ce, nuclei difficult to reach by large-scale SM calculations. Conclusions: Both pair correlation and the configuration mixing between different intrinsic states play a key role in reproducing collectivity and shape coexistence, demonstrating the utility of this truncation scheme of the SM to study transitional and deformed nuclei.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2026

Methods for Assessing Opportunities for Ring Dam Pumped Storage Hydropower

There is growing interest in new pumped storage hydropower (PSH) deployment to provide a range of grid flexibility, reliability, and resiliency services under an evolving and uncertain future power sector. The National Laboratory of the Rockies develops open PSH resource assessment and cost modeling tools to help evaluate PSH deployment opportunities, and this report describes expansions to those tools to consider an additional PSH system configuration - ring-dam reservoirs built on flat topographical features that are constructed from roller-compacted concrete material. This reservoir type is common among current PSH proposals and requires new methods to identify sites with this reservoir geometry throughout the United States and characterize the associated dam cost. Cost characterization for ring dam reservoirs required collecting historical dam cost data for earthen, rockfill, and roller-compacted concrete dams and regressing equations that relate costs between alternative materials. The ring dam site identification algorithm follows a 5-step procedure to identify circular geometry reservoirs. Once ring dam reservoirs are identified, they are then paired with potential dry-gully reservoirs, and the full set of potential paired reservoirs is cost-optimized to produce a least-cost set of potential PSH sites with no overlapping reservoirs. The resulting analysis found 1,663 ring-dam to dry-gully systems in the contiguous United States that are lower cost than any overlapping dry-gully to dry-gully systems, 29 in Alaska, and none in Hawaii or Puerto Rico. These systems constitute 1.5 TW of capacity in the contiguous United States and nearly 29 GW in Alaska, demonstrating that under suitable topography and head, ring-dam systems can provide cost-effective PSH opportunities. The greatest density of these opportunities are found in the intermountain west where there are mesas and flat land at bases of mountain ranges, but continued work could incorporate additional site characteristics or consider more complex reservoir shapes to find additional PSH deployment opportunities.

13 HYDRO ENERGY↗
DOE OSTI2023

Life cycle cost, energy, and carbon emissions of molds for precast concrete: Exploring the impacts of material choices and additive manufacturing

Molds for precast concrete are commonly used to create simple- to complex-shaped concrete products away from construction sites. These molds are often handmade from wood; however, additively manufacturing (AM, or 3D printing) fiber-reinforced polymer composites is an advantageous alternative, producing significantly more durable, highly complex molds faster, but likely at a higher cost. Here, this study explores the impact of material and production variables on the cost, energy, and carbon emissions of employing composite AM molds over the full lifecycle. The case study employed techno-economic and life cycle assessments to show that using wood flour–poly(lactic acid) or recycled carbon fiber–acrylonitrile butadiene styrene for AM molds can be less expensive than conventional wood molds, especially when considering use phase costs. While wood molds have the least environmental impacts due to wood's higher biogenic carbon sequestration and minimal processing, optimizing AM designs could reduce energy demand, carbon emissions, and cost.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Automating Bayesian inference and design to quantify acoustic particle levitation

Self-propulsion of micro- and nanoparticles powered by ultrasound provides an attractive strategy for the remote manipulation of colloidal matter using biocompatible energy inputs. Quantitative understanding of particle motion and its dependence on size, shape, and composition requires accurate characterization of the acoustic field, which depends sensitively on the experimental setup. Here, we show how automated experiments based on Bayesian inference and design can accurately and efficiently characterize the acoustic field within resonant chambers used to propel acoustic nanomotors. Repeated cycles of observation, inference, and design (OID) are guided by a physical model that describes the rate at which levitating particles approach the nodal plane. Using video microscopy, we observe the relaxation of tracer particles to this plane following the application of the acoustic field. We use sequential Monte Carlo methods to infer model parameters such as the amplitude and frequency of the resonant chamber while accounting for particle-level measurement noise and population-level heterogeneity in the field. Guided by simulated outcomes, we select the optimal design for the next experiment as to maximize the information gain in the relevant parameters. We show how this iterative process serves to discriminate between competing hypotheses and efficiently converges to accurate parameter estimates using only few automated experiments. We discuss the need for model criticism to ensure the validity of the guiding model throughout automated cycles of observation, inference, and design. Furthermore, this work demonstrates how Bayesian methods can learn the parameters of nonlinear, hierarchical models used to describe video microscopy data of active colloids.

42 ENGINEERING↗