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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.

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At least 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Rapid Initial-State Preparation for the Quantum Simulation of Strongly Correlated Molecules

Studies on quantum algorithms for ground-state energy estimation often assume perfect ground-state preparation; however, in reality the initial state will have imperfect overlap with the true ground state. Here, we address that problem in two ways: by faster preparation of matrix-product-state (MPS) approximations and by more efficient filtering of the prepared state to find the ground-state energy. We show how to achieve unitary synthesis with a Toffoli complexity about 7 × lower than that in prior work and use that to derive a more efficient MPS-preparation method. For filtering, we present two different approaches: sampling and binary search. For both, we use the theory of window functions to avoid large phase errors and minimize the complexity. We find that the binary-search approach provides better scaling with the overlap at the cost of a larger constant factor, such that it will be preferred for overlaps less than about 0.003 . Finally, we estimate the total resources to perform ground-state energy estimation of Fe - S cluster systems, including the Fe Mo cofactor by estimating the overlap of different MPS initial states with potential ground states of the Fe Mo cofactor using an extrapolation procedure. With a modest MPS bond dimension of 4000 , our procedure produces an estimate of approximately 0.9 overlap squared with a candidate ground state of the Fe Mo cofactor, producing a total resource estimate of 7.3 × 10 10 Toffoli gates; neglecting the search over candidates and assuming the accuracy of the extrapolation, this validates prior estimates that have used perfect ground-state overlap. This presents an example of a practical path to prepare states of high overlap in a challenging-to-compute chemical system. Published by the American Physical Society 2025

Berry, Dominic W. (ORCID:0000000334461449)↗
NASA NTRS2015

Characterization of Flap Edge Noise Radiation from a High-Fidelity Airframe Model

The results of an experimental study of the noise generated by a baseline high-fidelity airframe model are presented. The test campaign was conducted in the open-jet test section of the NASA Langley 14- by 22-foot Subsonic Tunnel on an 18%-scale, semi-span Gulfstream airframe model incorporating a trailing edge flap and main landing gear. Unsteady surface pressure measurements were obtained from a series of sensors positioned along the two flap edges, and far field acoustic measurements were obtained using a 97-microphone phased array that viewed the pressure side of the airframe. The DAMAS array deconvolution method was employed to determine the locations and strengths of relevant noise sources in the vicinity of the flap edges and the landing gear. A Coherent Output Power (COP) spectral method was used to couple the unsteady surface pressures measured along the flap edges with the phased array output. The results indicate that outboard flap edge noise is dominated by the flap bulb seal cavity with very strong COP coherence over an approximate model-scale frequency range of 1 to 5 kHz observed between the array output and those unsteady pressure sensors nearest the aft end of the cavity. An examination of experimental COP spectra for the inboard flap proved inconclusive, most likely due to a combination of coherence loss caused by decorrelation of acoustic waves propagating through the thick wind tunnel shear layer and contamination of the spectra by tunnel background noise at lower frequencies. Directivity measurements obtained from integration of DAMAS pressure-squared values over defined geometric zones around the model show that the baseline flap and landing gear are only moderately directional as a function of polar emission angle.

Humphreys, William M., Jr.↗
NASA NTRS2008

Crack Offset Measurement With the Projected Laser Target Device

The device and associated analysis methodology summarized in this report were developed for the purpose of estimating the size of discontinuities in the surface of the foam that covers the Space Shuttle External Tank. These surface offsets are thought to be due to subsurface cracks in the foam insulation. The mathematical analysis and procedure described here provide a method to quantity the dimensions of the crack offset in a direction perpendicular to the surface, making use of the projected laser target device (PLTD) tool and a laser line projector. The keys to the construction and use of the PLTD are the following geometrical design requirements: Laser dots are on a square grid: length on a side. Laser beams are perpendicular to projected surface. Beams are parallel out to the distance being projected. The PLTD can be used to (1) calibrate fixed cameras of unknown magnification and orientation (far-field solution); (2) provide equivalent calibration to multiple cameras, previously achieved only by the use of known target points, for example, in 3.D foreign-object debris tracking on a fixed launch platform; (3) compute scaling for conventional 2.D images, and depth of field for 3.D images (near-field solution); and (4) in conjunction with a laser line projector, achieve accurate measurements of surface discontinuity (cracks) in a direction perpendicular to the surface.

Source record↗
DOE OSTI2024

A quasi-meshfree method for constructing boundary-aware reproducing bases on geometrically complex domains using manifold geodesics

In many applications, physical domains are geometrically complex making it challenging to perform coarse-scale approximation. A defeaturing process is often used to simplify the domain in preparation for approximation and analysis at the coarse scale. In this paper, a methodology is presented for constructing a coarse-scale reproducing basis on geometrically complex domains given an initial fine-scale mesh of the fully featured domain. The initial fine-scale mesh can be of poor quality and extremely refined. The construction of the basis functions begins with a coarse-scale covering of the domain and generation of weighting functions with local support. Manifold geodesics are used to define distances within the local support for general applicability to non-convex domains. Conventional moving least squares is used to construct the coarse-scale reproducing basis. Applications in quasi-interpolation and linear elasticity are presented.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Thermoelastic properties of tungsten at simultaneous high pressure and temperature

In this work, the compressional ( P ) and shear wave velocities ( S ) and unit cell volumes (densities) of polycrystalline tungsten (W) have been measured simultaneously up to 10.5 GPa and 1073 K using ultrasonic interferometry in conjunction with x-ray diffraction and x-radiography techniques. Thermoelastic properties of W were derived using different methods. We obtained the isothermal bulk modulus K T 0 = 310.3(1.5) GPa, its pressure derivative K ' T 0 = 4.4(3), its temperature derivative at constant pressure ( ∂ K T / ∂ T ) P = – 0.0138 ( 1 ) GPa K – 1 and at constant volume ( ∂ K T / ∂ T ) V = – 0.0050 GPa K – 1 , the thermal expansion α ( 0, T ) = 1.02(27) × 10 –5 + 7.39(3.2) × 10 –9 T (K –1 ), as well as the pressure derivative of thermal expansion ( ∂ α / ∂ P ) T = – 1.44 ( 1 ) × 10 – 7 K – 1 GP a – 1 based on the high-temperature Birch–Murnaghan equation of state (EOS), the Vinet EOS, and thermal pressure approach. Finite strain analysis allowed us to derive the elastic properties and their pressure/temperature derivatives independent of the choice of pressure scale. A least-squares fitting yielded K S 0 = 314.5(2.5) GPa, K S 0 ' = 4.45(9), (∂ K S /∂ T ) P = – 0.0076(6) GPa K –1 , G 0 = 162.4(9) GPa, G 0 ' = 1.8(1), (∂ G /∂ T ) P = – 0.0175(9) GPa K –1 , and α 298 K = 1.23 × 10 – 5 K – 1 . Fitting current data to the Mie–Grüneisen–Debye EOS with derived θ 0 = 383.4 K yielded γ 0 = 1.81 ( 6 ) and q = 0.3 . The thermoelastic parameters obtained from various approaches are consistent with one another and comparable with previous results within uncertainties. Our current study provides a complete and self-consistent dataset for the thermoelastic properties of tungsten at high P – T conditions, which is important to improve the theoretical modeling of these materials under dynamic conditions.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Quantifying rupture characteristics of microearthquakes in the Parkfield Area using a high-resolution borehole network

It is well known that large earthquakes often exhibit significant rupture complexity such as well separated subevents. With improved recording and data processing techniques, small earthquakes have been found to exhibit rupture complexity as well. Studying these small earthquakes offers the opportunity to better understand the possible causes of rupture complexities. Specifically, if they are random or are related to fault properties. We examine microearthquakes (M < 3) in the Parkfield, California, area that are recorded by a high-resolution borehole network. We quantify earthquake complexity by the deviation of source time functions and source spectra from simple circular (omega-square) source models. We establish thresholds to declare complexity, and find that it can be detected in earthquakes larger than magnitude 2, with the best resolution above M2.5. Comparison between the two approaches reveals good agreement (>90 per cent), implying both methods are characterizing the same source complexity. For the two methods, 60–80 per cent (M 2.6–3) of the resolved events are complex depending on the method. The complex events we observe tend to cluster in areas of previously identified structural complexity; a larger fraction of the earthquakes exhibit complexity in the days following the M w 6 2004 Parkfield earthquake. Ignoring the complexity of these small events can introduce artefacts or add uncertainty to stress drop measurements. Focusing only on simple events however could lead to systematic bias, scaling artefacts and the lack of measurements of stress in structurally complex regions.

58 GEOSCIENCES↗
NASA NTRS2007

Fan Rig Noise Spectral Correction for NASA 9'x 15' Low-Speed Wind Tunnel

Aircraft engine noise research and development depends on the ability to study and predict the noise created by each engine component in isolation. Fan noise testing, however, requires a significant support system including a drive mechanism to turn the fan, a device to smooth the flow into the fan, and a stand to raise the fan off the ground each of which has the potential to create its own noise. A methodology was therefore developed to improve the data quality for the 9x15 Low Speed Wind Tunnel (LSWT) at the NASA Glenn Research Center that identifies three noise sources: fan noise, jet noise, and rig noise. The jet noise and rig noise was then measured by mounting a scale model of the 9x15 LSWT setup in a jet rig to simulate everything except the rotating machinery that characterizes fan noise. The data showed that the spectra measured in the LSWT has a strong rig noise component at frequencies as high as 3 kHz depending on the fan and speed. The jet noise was determined to be significantly lower than the rig noise. A mathematical model for the rig noise was then developed using a multi-dimensional least squares fit to the rig noise data. This allows the rig noise to be subtracted or removed, depending on the amplitude of the rig noise relative to the fan noise, at any given frequency, observer angle, or nozzle pressure ratio. The impact of isolating the fan noise with this method on spectra, overall power level (OAPWL), and Effective Perceived Noise Level (EPNL) is studied.

Schifer, Nick↗
NASA NTRS1994

Determining F-factor using ground-based Doppler radar: Validation and results

Using a two-dimensional linear least-squares method applied to Doppler radar data, we test the viability of determining F-factor remotely. The ultimate application of such an algorithm will be supplying real-time F-factor maps, derived from ground-based Doppler radars to air traffic control personnel and pilots. Data from NASA deployments to the MIT/Lincoln Lab TDWR testbed radar in Orlando in 1991 and 1992 along with NASA deployments to the NCAR TDWR testbed radar in Denver are examined. Preliminary analyses show that the two-dimensional method correlates reasonably well with in situ measurements. Several effects, independent of the method used, act to reduce the correlation to less than one. These include time differences between radar and aircraft data, vertical misalignment between the aircraft and the radar beam, different spatial resolution scales between aircraft and radar data, inhomogeneous radar beam filling, noise in radar data that eludes filtering, and phase lag between time and space due to low pass filtering of the aircraft data. In the final assessment, it appears that a shear-based F-factor algorithm is preferable to the currently implemented TDWR algorithms which lack any local shear estimates.

Elmore, K. L.↗
DOE OSTI2025

A machine learning method of modern urban building energy modeling: A case study of Chicago

Urban-scale building energy modeling is vital for urban planning. However, it can be challenging to assimilate reliable non-geometry building data for urban-scale modeling without extensive investment. Here, this study introduces a novel approach to developing modern urban-scale building energy stock data using geographic information systems and machine learning algorithms without necessarily requiring pre-supplied non-geometric metadata. The proposed framework integrates building footprint and height data to estimate gross floor areas, and matches each building to a pool of candidate records from ComStock or ResStock—filtered to the same county and ranked by geometric similarity—demonstrate a proof-of-concept case study in Chicago for predicting energy use intensity (EUI) using scalable datasets. The model achieved a mean bias error (MBE) of 0.08 kWh/m² and root mean square error (RMSE) of 14.84 kWh/m² under full metadata input for EUI prediction. With only location inputs, the model captured 69.2 % of EUI within predicted ranges. These results demonstrate the model’s potential to support early-stage urban planning, identify candidates for energy-efficient retrofits. By removing the dependency on detailed pre-surveys or extensive building metadata, the approach overcomes a key barrier in traditional urban-scale building energy modeling, illustrating a pathway toward broader and more cost-effective application, though further multi-city validation and improved treatment of pre-1925 buildings are needed.

Energy Use Intensity↗
DOE OSTI2024

A deep learning-based workflow for fast prediction of 3D state variables in geological carbon storage: A dimension reduction approach

Deep learning (DL) models are extensively used as surrogate models for high-fidelity simulations of multiphase fluid flow in porous media at large scales, enabling fast forecasts of the spatial–temporal evolution of three-dimensional (3D) state variables in geological carbon storage (GCS). However, training these models in high-dimensional space remains computationally demanding and prone to overfitting because of limited training data. This paper presents a novel workflow to address these challenges by integrating dimension reduction (DR) methods. Here, the proposed workflow employed pre-trained DR models to extract the latent variables of geological models and state variables and utilized the multi-layer perceptron (MLP) for constructing mapping functions between the input and output variables in latent spaces. Subsequently, the pre-trained reconstruction models converted the MLP-predicted latent state variables to their original high-dimensional form. Furthermore, we proposed a novel strategy for the DR and reconstruction of 3D saturation fields to account for the unique data characteristics of sparsity, nonuniformity, and discontinuity. The proposed strategy applied PCA and inverse PCA for 2D average saturation fields and developed a DL-based 3D reconstruction model, leveraging three 2D average saturation fields as input to produce a 3D saturation field as output. The pre-training of DR and reconstruction models and training of MLP models were conducted on 84 Gulf of Mexico (GoM) simulations and evaluated on 12 testing simulations. Each simulation contained 720 monthly time steps, with the first 360 months as the injection period and the rest as the post-injection period. The proposed workflow, incorporating DR and DL models, accurately predicts the normalized 3D pressure fields, achieving mean square error (MSE) of 2.92 × 10 -7 compared to the ground truth obtained from a full-physics simulator. Furthermore, the proposed strategy outperformed PCA and convolutional autoencoder (CAE) models on 3D saturation fields, resulting in minor workflow prediction errors with an MSE of 2.93 × 10 -5 . The results suggest the proposed workflow provides sufficient predictive fidelity across temporal and spatial scales, and enables a speedup of 160 times compared to the full-physics simulator, facilitating improved decision-making and risk assessment for large-scale GCS management in real-time scenarios.

3D reconstruction model↗
DOE OSTI2026

Correlating and Simulating Socio-Demographically Driven Residential End-Use Activity Schedules

Incorporating socio-demographic and behavioral considerations into decision-support tools is crucial for identifying gaps and addressing consumer needs to ensure reliable and affordable energy solutions. In energy simulation models, the correlation between socio-demographics and time-use behavior is not well-captured. Thus, we developed a large-scale simulation workflow to generate schedules for 10 residential activities across 24 population segments defined by age, income, and employment status. Using pre-pandemic 2015-2019 American Time Use Survey (ATUS) data, we used ANOVA to confirm the correlation between demographic factors and time use. We explored three k-modes clustering methods-backward, forward, and a new hybrid approach-to delineate the occupancy patterns based on demographics. Using the probability of cluster membership for each population segment and a time inhomogeneous Markov chain to generate activity transition probabilities for each cluster, we simulated 50,000 schedules per segment and validated them against the ATUS data. The hybrid method produced the most socio-demographically differentiated clusters while demonstrating comparable performance to other approaches, with an overall root mean square error of 0.12 for both weekday and weekend schedules. Thus, the hybrid method, where each cluster is dominated by certain demographic segments and occupancy patterns, offers more modeling versatility in terms of scenario analysis. The new workflow improves the socio demographic differentiation of energy consumption by considering differences in time use. This approach enables future research on demographically segmented time of use (TOU) energy consumption, including impacts of TOU utility bills and rate analysis, long-run marginal emissions, and energy retrofits.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS2010

Vertical Crustal Motion Derived from Satellite Altimetry and Tide Gauges, and Comparisons with DORIS Measurements

A somewhat unorthodox method for determining vertical crustal motion at a tide-gauge location is to difference the sea level time series with an equivalent time series determined from satellite altimetry, To the extent that both instruments measure an identical ocean signal, the difference will be dominated by vertical land motion at the gauge. We revisit this technique by analyzing sea level signals at 28 tide gauges that are colocated with DORIS geodetic stations. Comparisons of altimeter-gauge vertical rates with DORIS rates yield a median difference of 1.8 mm/yr and a weighted root-mean-square difference of2.7 mm/yr. The latter suggests that our uncertainty estimates, which are primarily based on an assumed AR(l) noise process in all time series, underestimates the true errors. Several sources of additional error are discussed, including possible scale errors in the terrestrial reference frame to which altimeter-gauge rates are mostly insensitive, One of our stations, Male, Maldives, which has been the subject of some uninformed arguments about sea-level rise, is found to have almost no vertical motion, and thus is vulnerable to rising sea levels. Published by Elsevier Ltd. on behalf of COSPAR.

Ray, R. D.↗
DOE OSTI2020

Plate motion in sheared granular fault system

Plate motion near the fault gouge layer, and the elastic interplay between the gouge layer and the plate under stick-slip conditions, is key to understanding the dynamics of sheared granular fault systems. Here, a two-dimensional implementation of the combined finite-discrete element method (FDEM), which merges the finite element method (FEM) and the discrete element method (DEM), is used to explicitly simulate a sheared granular gouge fault system. In this work we focus on investigating the influence of normal load, driving shear velocity and plate stiffness on the velocities and displacements in the direction parallel to the shear direction (x-direction) measured at locations on the upper and lower plates just adjacent to the gouge. The simulations show that during slip phases the magnitudes of the measured velocities on the upper and lower plates are proportional to the normal load and may be inversely proportional to the square root of the plate's shear modulus. Whereas, the driving shear velocity does not show distinct influence on the measured velocities. Additionally, large slip velocities are generally associated with large macroscopic friction coefficient drops. For the models subjected to smaller normal loads, larger shear velocities and with stiffer shear plates, the same magnitude of slip velocity could cause a larger drop of macroscopic friction coefficient. During stick phases, the velocities of the upper and lower plates are respectively slightly greater and slightly smaller than half of the driving shear velocity and are both in the same direction of shear. The shear strain rate of the gouge is calculated from this velocity difference between the upper and lower plate during stick phases and thus the gouge effective shear modulus can be calculated. The results show that the gouge effective shear modulus increases proportionally with normal load, while the influence of shear velocity and plate stiffness on gouge effective shear modulus is minor. The simulations address the dynamics of a laboratory-scale fault gouge system and may aid in revealing the complexities of earthquake frictional dynamics.

58 GEOSCIENCES↗
DOE OSTI2024

A novel conditional generative model for efficient ensemble forecasts of state variables in large-scale geological carbon storage

Integrating monitoring data to efficiently update reservoir pressure and CO 2 plume distribution forecasts presents a significant challenge in geological carbon storage (GCS) applications. Inverse modeling techniques are commonly used to fuse observational data and refine reservoir model parameters, thereby improving state variable forecasts. However, these techniques often rely on linear or Gaussian assumptions, which can limit their effectiveness in accurately predicting state variables. Moreover, simulating large-scale three-dimensional (3D) GCS problems is computationally expensive, making iterative runs in inverse problems prohibitive. To address these challenges, we propose a conditional generative model utilizing the score-based diffusion method for real-time 3D pressure and saturation field distribution predictions. Our approach involves solving the score function with a mini-batch-based Monte Carlo estimator to generate labeled data. This data is subsequently employed to train a fully connected neural network, enabling it to learn the conditional sample generator within a supervised learning framework. This method enables the rapid generation of a large ensemble of predictions, facilitating comprehensive uncertainty quantification of state variables. Here we applied our method to forecast the dynamic 3D distributions of pressure and saturation fields over a 30-year injection period. The statistical assessment with low root mean square error (RMSE) values demonstrates that our method can accurately predict the spatiotemporal distributions of both pressure and saturation fields. Moreover, the developed conditional generative model shows high computational efficiency by generating 100 ensemble forecasts of 3D state variables in less than 10 min. The consistency between ensemble averages and ground truth values further illustrates the model’s capability to capture state variable dynamics during the CO 2 plume injection process. Notably, the ground truth values fall within the ensemble forecasts, indicating that our uncertainty quantification effectively captures variability and potential noise in the observations. Thus, the developed conditional generative model proves to be a more efficient, accurate, and practical tool for GCS applications, facilitating timely risk analysis and informed decision-making.

58 GEOSCIENCES↗
NASA NTRS1987

Turbulence control on an airborne laser platform

An active flow control device to generate large-scale, periodic structures in a turbulent shear flow is developed. Together with adaptive optics, the device may be used on airborne laser platforms to reduce or eliminate optical distortion caused by the turbulence in the aircraft's boundary layer. A cyclic jet issuing from a spanwise slot is used to collect the turbulent boundary layer for a finite time and then release all of the flow instantaneously in one large eddy that convects downstream. Flow visualization and hot-film probe measurements are used together with pattern recognition algorithms to demonstrate the viability of the flow control method. A flat plate towed in a water channel is used as a test bed. The instantaneous velocity signal is used to compute important statistical quantities of the random velocity field, such as the mean, the root-mean-square, the spectral distribution, and the probability density function. When optimized for a given boundary layer, it is shown that the cyclic jet will produce periodic structures that are similar to the random, naturally occurring ones. These structures seem to trigger the onset of bursting events near the wall of the plate. Thus, the present device generates periodic structures in both the outer and inner regions of a turbulent boundary layer.

Gad-El-hak, Mohamed↗
DOE OSTI2021

Simulating Large PEPs Tensor Networks on Small Quantum Devices

We systematically map low bond dimension PEPs tensor networks to quantum circuits. By measuring and reusing qubits, we are in principle able to simulate an N×M square lattice PEPs network (for arbitrary M) of bond dimension 2 using N+ 2 qubits. We then seek to determine if this mapping can yield useful values for long-range loop observables in the presence of quantum device noise in the topological Wen plaquette model by mapping a 3×3 PEPs tensor network to a 5-qubit quantum circuit and executing it on the Honeywell System Model H1-1 trapped-ion device. We find that, for this system size, the noisy observable values are indeed sufficient for diagnosing topological vs. trivial order as the Wen model is perturbed by a magnetic field term in the Hamiltonian. We provide an overview of the experimental procedure and its results. We then explain in greater detail our method for mapping 2D tensor networks to quantum circuits and its scaling properties. This serves as a proof-of-concept of the utilty of the measure-and-reuse approach for simulating large 2D quantum systems on small quantum devices.

MacCormack, Ian↗
DOE OSTI2025

In situ Monitoring of Lanthanide Reactions with Oxide Species via Combined Absorption Spectroscopy and Electrochemical Methods

Molten salts for engineering scale applications of spent nuclear fuel pyrochemical processing will inevitably have some level of oxygen impurities which can form insoluble oxide and oxychloride species with fission products. This work demonstrates real-time concentration monitoring of two lanthanide (Ln3+) fission products, Nd3+ and Pr3+, and their reactions with oxygen (O2-) impurities to form insoluble products in LiCl-NaCl-KCl eutectic salt. Combined absorption spectroscopy and electrochemical testing were used to track lanthanide concentrations. O2- impurity levels were controlled by adding Li2O to lanthanide-salt solutions. After the introduction of O2- impurities, Ln3+ concentrations were monitored via time-resolved absorption spectroscopy. Concentrations of both Ln3+ species in solution decreased with time as insoluble products formed. The initial impurity concentration controlled whether insoluble products were predominantly oxychlorides or mixtures of oxychlorides and oxides. However, absorption spectroscopy is limited for weakly absorbing species, such as Pr3+, and under conditions of high impurity concentrations where solutions can be turbid. To circumvent this limitation, the concentrations of Pr3+ were monitored with square wave voltammetry (SWV). Reaction rates and extent of Pr3+ removal from solution as monitored by SWV agreed closely with results found from spectroscopic monitoring. This demonstrates that simultaneous electrochemical testing complements the capabilities of absorption spectroscopy to monitor reactions of fission products in molten salts.

absorption spectroscopy↗
DOE OSTI2019

A two-phase substrate model for enzymatic hydrolysis of lignocellulose: application to batch and continuous reactors

Abstract Background Enzymatic hydrolysis continues to have a significant projected production cost for the biological conversion of biomass to fuels and chemicals, motivating research into improved enzyme and reactor technologies in order to reduce enzyme usage and equipment costs. However, technology development is stymied by a lack of accurate and computationally accessible enzymatic-hydrolysis reaction models. Enzymatic deconstruction of cellulosic materials is an exceedingly complex physico-chemical process. Models which elucidate specific mechanisms of deconstruction are often too computationally intensive to be accessible in process or multi-physics simulations, and empirical models are often too inflexible to be effectively applied outside of their batch contexts. In this paper, we employ a phenomenological modeling approach to represent rate slowdown due to substrate structure (implemented as two substrate phases) and feedback inhibition, and apply the model to a continuous reactor system. Results A phenomenological model was developed in order to predict glucose and solids concentrations in batch and continuous enzymatic-hydrolysis reactors from which liquor is continuously removed by ultrafiltration. A series of batch experiments were performed, varying initial conditions (solids, enzyme, and sugar concentrations), and best-fit model parameters were determined using constrained nonlinear least-squares methods. The model achieved a good fit for overall sugar yield and insoluble solids concentration, as well as for the reduced rate of sugar production over time. Additionally, without refitting model coefficients, good quantitative agreement was observed between results from continuous enzymatic-hydrolysis experiments and model predictions. Finally, the sensitivity of the model to its parameters is explored and discussed. Conclusions Although the phenomena represented by the model correspond to behaviors that emerge from clusters of mechanisms, and hence a set of model coefficients are unique to the substrate and the enzyme system, the model is efficient to solve and may be applied to novel reactor schema and implemented in computational fluid dynamics (CFD) simulations. Hence, this modeling approach finds the right balance between model complexity and computational efficiency. These capabilities have broad application to reactor design, scale-up, and process optimization.

09 BIOMASS FUELS↗