Open-source MATLAB Code Research Articles

FreeTO - Freeform 3D topology optimization using a structured mesh with smooth boundaries in Matlab

Topology optimization has revolutionized the design of structures for various applications, particularly with the advancement of additive manufacturing. However, existing open-source codes for topology optimization have limitations, such as restricted domain initialization and lack of a CAD output after optimization. A novel open-source Matlab code, FreeTO, is presented, and it addresses these limitations by enabling the initialization of 3D arbitrary geometries and providing an STL file post-optimization. FreeTO utilizes a structured mesh and a smooth-edge (boundary) algorithm to generate smooth topological boundaries. The code is demonstrated through six practical design cases, showcasing its effectiveness in compliance minimization, compliant mechanisms, and self-supporting problems. FreeTO offers a user-friendly, all-in-one topology optimization package, making it an invaluable tool for educators, researchers, and practitioners. Future developments will focus on eliminating a few geometrical deviations in the optimized topologies, incorporating speedups, and extending the code to apply to more applications.

SCTBEM: A scaled coordinate transformation boundary element method with 99-line MATLAB code for solving Poisson's equation

This study introduces the scaled coordinate transformation boundary element method (SCTBEM), a novel boundary-type method for solving three-dimensional potential problems. To apply the BEM to complex problems, it is common practice to use the fundamental solution corresponding to the partial governing equation operator to establish the integral equation. However, this approach introduces the domain integral, which may jeopardize the dimensionality reduction advantages of BEM. To preserve the benefits of dimensionality reduction, this study proposes a novel domain integral transformation method named SCT. The SCT is purely a mathematical operation that does not rely on a particular solution of the operators, which requires only discretization on the surface of the structure while remaining analytical in the radial direction. An even more significant advantage is that the lower-order singularity can be eliminated by the coordinate translation technique. To facilitate the wider adoption of BEM, the authors present an open-source 99-line MATLAB code. Numerical results demonstrate that the SCTBEM exhibits high numerical accuracy even when dealing with complex models.

Receive coil quality assurance procedure and automated analysis for ViewRay MRIdian MR-Linac.

Regular receiving coil quality assurance (QA) is required to ensure image quality of an MRIdian Linac system. The manufacturer provides a spherical phantom and positioning tube for single-slice signal-to-noise ratio (SNR) and uniformity assessments. We aimed to improve imaging setup and coverage and eliminate inter-scan variability by employing multi-slice imaging of a stable phantom. Additionally, we strived to expedite analysis by developing objective, automated analysis software. A 5300mL cylindrical plastic bottle placed in plastic bins was scanned at isocenter using a spin-echo sequence with NEMA-recommended parameters and 18 axial slices, avoiding phantom repositioning. Acquisition was repeated with and without prescan normalization filtering and by saving uncombined element images. Obtained data were analyzed using custom open-source MATLAB code. Signal and noise images were automatically assigned, and ROIs for SNR and uniformity calculations were defined using image thresholding. SNR and uniformity pass/fail decisions were made using baseline comparisons. The proposed method was successfully implemented as monthly coil QA for 3.5 years. Setup and scanning took 41 min on average for a coil set. Automated image analysis was completed in a few minutes. Signal intensity peaked around +90 or -90mm for Torso or Head/Neck coil unfiltered images. Noise peaked and minimized SNR inside±30mm from isocenter, while maximizing it around±130mm. Prescan normalization smoothed signal response, reduced SNR and increased uniformity. Individual coil element image analysis identified their position, signal or noise response and SNR. SNR and uniformity pass/fail thresholds were set for already tested and new coils. Conspicuous and subtle Torso coil malfunctions were detected considering baseline deviations of combined and individual element results. Our QA method eliminated observer bias and provided insights into coil function, image filtering performance and coil element location. It provided SNR and uniformity thresholds and identified faulty coil elements.

An advanced median filter for improving the signal-to-noise ratio of seismological datasets

Strong noise usually disturbs the recorded seismic waves, resulting in low-quality seismic data sometimes with an extremely low signal-to-noise ratio (S/N), which negatively impacts the subsequent seismological processes, e.g., imaging, inversion, and interpretation. Suppressing undesirable noise is a meaningful procedure to increase the S/N of seismological datasets. This issue can be partially addressed using the recently proposed structure-oriented space-varying median filter (SOSVMF) by filtering out the unwanted noise from noise-corrupted signals. However, the SOSVMF approach has limitations when the raw data is corrupted by various sources of noise which is more common in practice. To conquer the difficulties in improving the S/N in the face of diverse types of strong noise, we introduce MATamf, an open-source MATLAB code package based on a novel advanced median filter (AMF). The proposed AMF workflow takes advantage of multiple denoising operators, i.e., the bandpass (BP) filter, SOSVMF, dip filter in the frequency–wavenumber (FK) domain, Curvelet, and local orthogonalization (LO), all in the same framework to simultaneously attenuate all types of noise and improve S/N. To demonstrate the usefulness of the MATamf package and its advantage over conventional denoising methods, we introduce the principles behind the proposed AMF framework and present results from a variety of seismological problems, including seismic reflection, distributed acoustic sensing (DAS), as well as global seismological tasks of receiver function and SS-precursors imaging. All results show that the proposed AMF workflow can be conveniently utilized to improve the S/N of a wide spectrum of seismological applications.

Effective fluence and dose at skin depth of daylight and lamp sources for PpIX-based photodynamic therapy.

Skin-based photodynamic therapy (PDT) is used for the clinical treatment of actinic keratosis (AKs) and other skin lesions with continued expansion into the standard of care. Due to the spectral dependency of photosensitizer activation and skin optical fluence, there is a need for more accurate methods to estimate the delivered dose at depth from different PDT light sources and treatment regimens. Develop radiometric methods for calculating photosensitizer-effective fluence and dose at depth and determine differences between red-lamp, blue-lamp, and daylight-based PDT treatments. Radiometric measurements of FDA-approved PDT lamp sources, outdoor daylight, and indoor daylight were performed for clinically relevant AK treatments. The protoporphyrin IX (PpIX) equivalent irradiance, fluence, and dose for each light source were calculated from the PpIX absorption spectrum and a 7-layer skin fluence model. The effective fluence and dose at depth was estimated by combining the spectral attenuation predicted at each wavelength and depth with the source fluence at each wavelength. The red-lamp source had the highest illuminance (112,000lumen/m2), but lowest PpIX-effective irradiance (9.6W/m2), and highest effective fluence at depth (10.8W/m2 at 500µm). In contrast, the blue light source had the lowest illuminance (2300lumen/m2), but highest PpIX effective irradiance (37.0W/m2), and ultimately the lowest effective fluence at depth (0.18W/cm2 at 500µm). The daylight source had values of (outdoor | indoor) illuminance of (49,200 | 37,800 lumen/m2), effective irradiance of (19.2 | 10.7W/m2), and effective fluence of (1.50 | 1.08W/m2 at 500µm). The effective fluence and dose at depth facilitated the comparison of treatment regimens, for example, calculating an equivalent dose for a 2 hr indoor daylight treatment and a 10min red-light treatment for the 300-1000μm depth range. The consideration of PpIX-effective fluence at varying depths is necessary to provide adequate comparisons of the delivered dose from PDT light sources. Methods for calculating radiometric fluence and delivered dose at depth were introduced, with open source MATLAB code, to help overcome the limitations of commonly used photometric and irradiance-based reporting.

Flux and Loss Map Based Evaluation of the Efficiency Map of Synchronous Machines

This article presents a methodology for the efficiency maps evaluation of synchronous electric machines. The procedure is based on the manipulation of flux linkage, iron and PM loss maps obtained via 2D magneto-static Finite-Element Analysis. The paper thoroughly describes the procedure and its key computational steps, all referring to open-source Matlab code available to the public. A method for iron loss evaluation from magneto-static FEA is proposed, valid for both sinusoidal and PWM supply. Experimental results are provided for the validation of single loss terms calculation and for the whole efficiency map, with reference to an interior permanent magnet machine designed for traction. FEA evaluation of PWM supply conditions relies on the off-line computation of the motor phase currents using a custom PLECS model of the drive, still flux-map based. This step of the procedure is also validated experimentally. The proposed methodology covers permanent magnet synchronous and synchronous reluctance machines, and finds prominent application in the automotive field, for traction and on-board generation.

Kinematic Modeling and Motion Planning of the Mobile Manipulator Agri.Q for Precision Agriculture

In recent years, the study of robotic systems for agriculture, a modern research field often shortened as “precision agriculture”, has become highly relevant, especially for those repetitive actions that can be automated thanks to innovative robotic solutions. This paper presents the kinematic model and a motion planning pipeline for a mobile manipulator specifically designed for precision agriculture applications, such as crop sampling and monitoring, formed by a novel articulated mobile base and a commercial collaborative manipulator with seven degrees of freedom. Starting from the models of the two subsystems, characterized by an adjustable position and orientation of the manipulator with respect to the mobile base, the linear mapping that describes the differential kinematics of the whole custom system is expressed as a function of the input commands. To perform pick–and–place tasks, a motion planning algorithm, based on the manipulator manipulability index mapping and a closed form inverse kinematics solution is presented. The motion of the system is based on the decoupling of the base and the arm mobility, and the paper discusses how the base can be properly used for manipulator positioning purposes. The closed form inverse kinematics solution is also provided as an open-source Matlab code.

A MATLAB code package for 2D/3D local slope estimation and structural filtering

Local slope is an important attribute that can help distinguish seismic signals from noise. Based on optimal slope estimation, many filtering methods can be designed to enhance the signal-to-noise ratio of noisy seismic data. We present an open-source MATLAB code package for local slope estimation and corresponding structural filtering. This package includes 2D and 3D examples with two main executable scripts and related subfunctions. All code files are in the MATLAB format. In each main script, local slope is estimated based on the well-known plane-wave destruction algorithm. Then, the seismic data are transformed to the flattened domain by utilizing this slope information. Furthermore, the smoothing operator can be effectively applied in the flattened domain. We introduce the theory and mathematics related to these programs and present the synthetic and field data examples to show the usefulness of this open-source package. The results of local slope estimation and structural filtering demonstrate that this package can be conveniently and effectively applied to the seismic signal analysis and denoising.

Rendering neuronal state equations compatible with the principle of stationary action

The principle of stationary action is a cornerstone of modern physics, providing a powerful framework for investigating dynamical systems found in classical mechanics through to quantum field theory. However, computational neuroscience, despite its heavy reliance on concepts in physics, is anomalous in this regard as its main equations of motion are not compatible with a Lagrangian formulation and hence with the principle of stationary action. Taking the Dynamic Causal Modelling (DCM) neuronal state equation as an instructive archetype of the first-order linear differential equations commonly found in computational neuroscience, we show that it is possible to make certain modifications to this equation to render it compatible with the principle of stationary action. Specifically, we show that a Lagrangian formulation of the DCM neuronal state equation is facilitated using a complex dependent variable, an oscillatory solution, and a Hermitian intrinsic connectivity matrix. We first demonstrate proof of principle by using Bayesian model inversion to show that both the original and modified models can be correctly identified via in silico data generated directly from their respective equations of motion. We then provide motivation for adopting the modified models in neuroscience by using three different types of publicly available in vivo neuroimaging datasets, together with open source MATLAB code, to show that the modified (oscillatory) model provides a more parsimonious explanation for some of these empirical timeseries. It is our hope that this work will, in combination with existing techniques, allow people to explore the symmetries and associated conservation laws within neural systems – and to exploit the computational expediency facilitated by direct variational techniques.

Design and implementation of an open-source MATLAB code for GNSS/MEMS-INS deep integrated navigation

In recent years, the research regarding Global Navigation Satellite System (GNSS) / MEMS (Micro-Electro-Mechanical System)-Inertial Navigation System(INS) Deep Integrated (DI) navigation has aroused widespread concern. The DI navigation method can significantly improve the dynamic performance and anti-interference ability of the GNSS receiver in scenarios such as high dynamics and weak signals. On the one hand, the estimated parameters of the GNSS/MEMS-INS integrated navigation filter can be adopted to improve the shortcomings of INS system error divergence over time. On the other hand, the MEMS-INS enhances tracking sensitivity and accuracy by compressing bandwidth to assist the GNSS receiver tracking loop. In this paper, we present the open source matlab code of the GNSS/MEMS-INS DI method. It provides a basic framework to facilitate researchers and scientists to investigate its pros and cons in a variety of complex scenarios. In order to achieve this goal, the implementation details of the developed algorithm are described, which is conducive to the rapid implementation and evaluation of the users’ new algorithm related to DI. Finally, the experiment was carried out to show the usage and performance of the provided code in a high dynamic scene.

Distributed power flow and distributed optimization—Formulation, solution, and open source implementation

Solving the power flow problem in a distributed fashion empowers different grid operators to compute the overall grid state without having to share grid models—this is a practical problem to which industry does not have off-the-shelf answers. We propose two physically consistent problem formulations (a feasibility and a least-squares formulation) amenable to two solution methods from distributed optimization: the Alternating direction method of multipliers ( admm ), and the Augmented Lagrangian based Alternating Direction Inexact Newton method ( aladin ); the latter comes with convergence guarantees. In addition, we provide open source matlab code for rapid prototyping for distributed power flow (rapid pf ): a fully matpower -compatible software that facilitates the laborious task of formulating power flow problems as distributed optimization problems. Simulation results for systems ranging from 53 buses (with 3 regions) up to 4662 buses (with 5 regions) show that the least-squares formulation solved with aladin requires just about half a dozen coordinating steps before the power flow problem is solved.

DeepMIB: User-friendly and open-source software for training of deep learning network for biological image segmentation.

We present DeepMIB, a new software package that is capable of training convolutional neural networks for segmentation of multidimensional microscopy datasets on any workstation. We demonstrate its successful application for segmentation of 2D and 3D electron and multicolor light microscopy datasets with isotropic and anisotropic voxels. We distribute DeepMIB as both an open-source multi-platform Matlab code and as compiled standalone application for Windows, MacOS and Linux. It comes in a single package that is simple to install and use as it does not require knowledge of programming. DeepMIB is suitable for everyone interested of bringing a power of deep learning into own image segmentation workflows.

A tutorial and open source software for the efficient evaluation of gravity and magnetic kernels

Fast computation of three-dimensional gravity and magnetic forward models is considered. When the measurement data is assumed to be obtained on a uniform grid which is staggered with respect to the discretization of the parameter volume, the resulting kernel sensitivity matrices exhibit block-Toeplitz–Toeplitz-block (BTTB) structure. These matrices are symmetric for the gravity problem but unsymmetric for the magnetic problem. In each case, the structure facilitates fast forward computation using two-dimensional fast Fourier transforms. The construction of the kernel matrices and the application of the transform for fast forward multiplication, for each problem, is carefully described. But, for purposes of comparison with the non-transform approach, the generation of the unique entries that define a given kernel matrix is also explained. It is also demonstrated how the matrices, and hence transforms, are adjusted when padding around the volume domain is introduced. The transform algorithms for fast forward matrix multiplication with the sensitivity matrix and its transpose, without the direct construction of the relevant matrices, are presented. Numerical experiments demonstrate the significant reduction in computation time and memory requirements that are achieved using the transform implementation. Thus, it becomes feasible, both in terms of reduced memory requirements and computational time, to implement the transform algorithms for large three-dimensional volumes. All presented algorithms, including with variable padding, are coded for optimal memory, storage and computation as an open source Matlab code which can be adapted for any convolution kernel which generates a BTTB matrix, whether or not it is symmetric. This work, therefore, provides a general tool for the efficient simulation of gravity and magnetic field data, as well as any formulation which admits a sensitivity matrix with the required structure.

Tutorial: The discrete-sectional method to simulate an evolving aerosol

The discrete-sectional method to solve the general dynamic equations is a useful tool for the simulation of an evolving aerosol population. This tutorial is intended to equip the reader with the necessary knowledge to implement this method for a single component system. To this end, we provide step-by-step instructions on the construction of a discrete-sectional model, including details on simulation bin configurations and all the necessary equations to describe relevant physical processes in an aerosol, i.e. condensation/evaporation, coagulation, and external particle losses. Supplementary to the text is a functional, open source MATLAB code that implements the framework introduced in this tutorial. The interested readers can use the code either for learning purposes or to meet research demands. Lastly, we designed six test cases not only to verify the validity of our discrete-sectional model, but also to help the reader gain insight into the evolution of aerosol systems.

1D electromagnetic response modeling with arbitrary source-receiver geometry based on vector potential and its implementation in MATLAB

The calculation of 1D electromagnetic (EM) responses of dipole sources is considered as a fundamental computation kernel in several geophysical applications, ranging from EM sensitivity analysis to high-dimensional EM forward modeling and inversion. To solve the EM responses caused by electric and magnetic dipoles with different orientations, we have developed an open-source MATLAB code for a complete treatment, which allows for an arbitrary transmitter-receiver geometry in the multilayered earth. A complete derivation of the EM field expressions with simplified exponent terms for all traditional dipole sources is accomplished based on the vector potential differential equations. The quadrature-with-extrapolation algorithm is adapted for calculating the integration of Bessel functions to produce EM responses with a desired accuracy. The MATLAB digit functions are used to alleviate the instability problem caused by the exponent terms. The accuracy of our code is verified by comparing the results with the published data and self-checks on an infinite thin sheet. A layered model is designed to test the capability of our code for all traditional dipole sources by placing the receiver at different depths. In the end, we apply our code to marine and airborne controlled-source EM explorations. The results indicate that our code is accurate and can potentially be used to calculate 1D EM responses for general EM problems.

Numerical Study on Flow Around Modern Ship Hulls with Rudder-Propeller Interactions

Reducing the fuel consumption of ships presents both economic and environmental gains. Although in the past decades, extensive studies were carried out on the flow around ship hull, it is still difficult to calculate the flow around the hull while considering propeller interaction. In this paper, the viscous flow around modern ship hulls is computed considering propeller action. In this analysis, the numerical investigation of flow around the ship is combined with propeller theory to simulate the hull-propeller interaction. Various longitudinal positions of the rudder are also analyzed to determine the effect of rudder position on propeller efficiency. First, a numerical study was performed around a bare hull using Shipflow computational fluid dynamics (CFD) code to determine free-surface wave elevation and resistance components. A zonal approach was applied to successively incorporate “potential flow solver” in the region outside the boundary layer and wake, “boundary layer solver” in the thin boundary layer region near the ship hull, and “Navier-Stokes solver” in the wake region. Propeller open water characteristics were determined using an open-source MATLAB code OpenProp, which is based on the lifting line theory, for the moderately loaded propeller. The obtained open water test results were specified in the flow module of Shipflow for self-propulsion tests. The velocity field behind the ship was recalculated into an effective wake and given to the propeller code that calculates the propeller load. Once the load was known, it was transferred to the Reynolds-averaged Navier-Stokes (RANS) solver to simulate the propeller action. The interaction between the hull and propeller with different rudder positions was then predicted to improve the propulsive efficiency.

SynSing: open-source MATLAB code for generating synthetic signals in studies of animal acoustic communication

ABSTRACT Synthetic, computer-generated signals are widely used in playback studies of animal acoustic communication. Depending on the goals of the experimenter, they can offer several significant advantages over playbacks of recordings of edited or unedited natural signals. However, there are few ‘off the shelf’ software options for the bioacoustician interested in synthesizing signals that combine ease of use with versatility. Here, we introduce SynSing, a free, open-source graphical user interface (GUI) for generating synthetic acoustic and seismic signals in MATLAB for use in playback studies of animal acoustic communication. Following a brief overview of the GUI, we describe how users can specify a variety of spectral properties (e.g., fundamental frequency, relative amplitudes and starting phases of harmonic and inharmonic components, frequency modulation) and temporal properties (e.g., pulse, note, or call duration and rate, onset and offset characteristics of amplitude envelopes) to generate individual signals or long sequences of repeated signals. We demonstrate SynSing’s versatility by reconstructing synthetic signals from published studies of several frogs, a field cricket, a katydid, a grasshopper, and a spider. We also provide worked examples of simple birdsong, as well as pure tones, linear frequency modulated sweeps, and noise.

A model of the entrance pupil of the human eye

The aperture of the iris is subject to refraction by the cornea, and thus an outside observer sees a virtual image: the pupil of the eye. When viewed off-axis, the entrance has an elliptical form. The precise appearance of the entrance is the consequence of the anatomical and optical properties of the eye, and the relative positions of the eye and the observer. This paper presents a ray-traced, exact model eye that provides the parameters of the entrance ellipse for an observer at an arbitrary location. The model is able to reproduce empirical measurements of the shape of the entrance with good accuracy. I demonstrate that accurate specification of the entrance of a stationary eye requires modeling of corneal refraction, the misalignment of the visual and optical axes, and the non-circularity of the aperture. The model, including a three-dimensional ray-tracing function through quadric surfaces, is implemented in open-source MATLAB code.

A model of the entrance pupil of the human eye

The aperture stop of the iris is subject to refraction by the cornea, and thus an outside observer sees a virtual image: the “entrance pupil” of the eye. When viewed off-axis, the entrance pupil has an elliptical form. The precise appearance of the entrance pupil is a consequence of the anatomical and optical properties of the eye, and the relative positions of the eye and the observer. This paper presents a ray traced model eye that provides the parameters of the entrance pupil ellipse for an observer at an arbitrary location. The model is able to reproduce empirical measurements of the shape of the entrance pupil with good accuracy. I demonstrate that accurate specification of the entrance pupil of a stationary eye requires modeling of corneal refraction, the misalignment of the visual and optical axes, and the non-circularity of the aperture stop. The model, including a three-dimensional ray tracing function through quadric surfaces, is implemented in open-source MATLAB code.

Permutation Statistics for Connectivity Analysis between Regions of Interest in EEG and MEG Data

Connectivity estimates based on electroencephalography (EEG) and magnetoencephalography (MEG) are unique in their ability to provide neurophysiologically meaningful spectral and temporal information non-invasively. This multi-dimensional aspect of the MEG/EEG based connectivity increases the challenges of the analysis and interpretation of the data. Many MEG/EEG studies address this complexity by using a hypothesis-driven approach, which focuses on particular regions of interest (ROI). However, if an effect is distributed unevenly over a large ROI and variable across subjects, it may not be detectable using conventional methods. Here, we propose a novel approach, which enhances the statistical power for weak and spatially discontinuous effects. This results in the ability to identify statistically significant connectivity patterns with spectral, temporal, and spatial specificity while correcting for multiple comparisons using nonparametric permutation methods. We call this new approach the Permutation Statistics for Connectivity Analysis between ROI (PeSCAR). We demonstrate the processing steps with simulated and real human data. The open-source Matlab code implementing PeSCAR are provided online.