Search arXivSearch

arXiv subjects

William Wallace

Publications and source records attributed to William Wallace.

2 recordsLinked to original sources

A Calibrated Reduced-Order Force Model for Bacterial Hydrodynamics in Free Space and Near a Planar Boundary

Accurately resolving the near-field flow generated by many swimming bacteria while retaining computational efficiency remains challenging. Stokeslet-based models with many force points can capture detailed near-field hydrodynamics but are computationally expensive. Other approaches include far-field and low-order models that use fewer points but sacrifice near-field accuracy. We introduce a reduced-order framework based on the method of regularized Stokeslets that preserves important near-field flow features while using substantially fewer force points. The method replaces the force distribution of a high-fidelity model with forces on a sparse set of points whose strengths are determined by constrained least-squares calibration to the high-fidelity velocity field of a single bacterium. The calibrated forces yield an approximation that preserves the dominant reference-flow structure while satisfying the force-free and torque-free conditions of self-propelled swimming. Principal component analysis is then used to represent the phase-dependent variation of the calibrated forces using only a few dominant modes. By fitting the corresponding modal coefficients as continuous functions of flagellar phase, the reduced-order forces can be approximated at any phase of the flagellar cycle. The framework is applied in both free space and near a no-slip planar boundary, where it preserves the dominant flow structures and captures the wall-induced redirection of the surrounding fluid. The optimized cell-body regularization parameter depends weakly on wall distance, and the remaining velocity discrepancy is concentrated primarily near the cell body. By substantially reducing the number of force points, the reduced-order model lowers both the computational cost and memory requirements of velocity-field evaluation, making large-domain simulations of multi-swimmer flow fields more practical.

physics.flu-dyn

KloakDB: A Platform for Analyzing Sensitive Data with $K$-anonymous Query Processing

A private data federation enables data owners to pool their information for querying without disclosing their secret tuples to one another. Here, a client queries the union of the records of all data owners. The data owners work together to answer the query using privacy-preserving algorithms that prevent them from learning unauthorized information about the inputs of their peers. Only the client, and a federation coordinator, learn the query's output. KloakDB is a private data federation that uses trusted hardware to process SQL queries over the inputs of two or more parties. Currently private data federations compute their queries fully-obliviously, guaranteeing that no information is revealed about the sensitive inputs of a data owner to their peers by observing the query's instruction traces and memory access patterns. Oblivious querying almost always exacts multiple orders of magnitude slowdown in query runtimes compared to plaintext execution, making it impractical for many applications. KloakDB offers a semi-oblivious computing framework, $k$-anonymous query processing. We make the query's observable transcript $k$-anonymous because it is a popular standard for data release in many domains including medicine, educational research, and government data. KloakDB's queries run such that each data owner may deduce information about no fewer than $k$ individuals in the data of their peers. In addition, stakeholders set $k$, creating a novel trade-off between privacy and performance. Our results show that KloakDB enjoys speedups of up to $117$X using k-anonymous query processing over full-oblivious evaluation.

cs.DB