Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “linear 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 1,711 records · Page 95
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

SU-E-T-197: Helical Cranial-Spinal Treatments with a Linear Accelerator

Purpose: Craniospinal irradiation (CSI) of systemic disease requires a high level of beam intensity modulation to reduce dose to bone marrow and other critical structures. Current helical delivery machines can take 30 minutes or more of beam-on time to complete these treatments. This pilot study aims to test the feasibility of performing helical treatments with a conventional linear accelerator using longitudinal couch travel during multiple gantry revolutions. Methods: The VMAT optimization package of the Eclipse 10.0 treatment planning system was used to optimize pseudo-helical CSI plans of 5 clinical patient scans. Each gantry revolution was divided into three 120° arcs with each isocenter shifted longitudinally. Treatments requiring more than the maximum 10 arcs used multiple plans with each plan after the first being optimized including the dose of the others (Figure 1). The beam pitch was varied between 0.2 and 0.9 (couch speed 5- 20cm/revolution and field width of 22cm) and dose-volume histograms of critical organs were compared to tomotherapy plans. Results: Viable pseudo-helical plans were achieved using Eclipse. Decreasing the pitch from 0.9 to 0.2 lowered the maximum lens dose by 40%, the mean bone marrow dose by 2.1% and the maximum esophagus dose by 17.5%. (Figure 2). Linac-based helical plans showed dose results comparable to tomotherapy delivery for both target coverage and critical organ sparing, with the D50 of bone marrow and esophagus respectively 12% and 31% lower in the helical linear accelerator plan (Figure 3). Total mean beam-on time for the linear accelerator plan was 8.3 minutes, 54% faster than the tomotherapy average for the same plans. Conclusions: This pilot study has demonstrated the feasibility of planning pseudo-helical treatments for CSI targets using a conventional linac and dynamic couch movement, and supports the ongoing development of true helical optimization and delivery.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2026

Maximizing dynamic range and performance of anatase TiO 2 ECRAM through structure and programming

Here, in this study, we investigate the structure-dependent modulation characteristics of all-solid-state three-terminal electrochemical random-access memory (ECRAM) based on an anatase Li x TiO 2 channel. By directly comparing “asymmetric” and “symmetric” ECRAM device architectures, we reveal significant insight into the impact of a non-zero gate-drain open-circuit voltage and its influence on voltage vs. current-controlled gating. We also explore the impact of potentiation/depression write parameters on the symmetry, linearity, and dynamic range of the device response. Together, initial results from optimizing structure and programming approaches yielded unprecedented G max /G min ratios of >1,000 for ECRAM and hundreds of tunable memory states with excellent linearity and symmetry. Simulations based on these ECRAM devices further illustrate the promise of this analog memory technology, achieving near 2% classification error in the MNIST digit recognition benchmark for a range of training parameters compared to a theoretical best of 1.66% and outperforming other device models extracted from the literature.

AIHWKit↗
NASA NTRS1983

Optimal processing of satellite-derived magnetic anomaly data

It is shown how the concept of the power spectrum can be extended to two-dimensional spatial power spectra and how it can be used in determining optimal data processing methods for satellite-derived magnetic anomaly data and planning missions to obtain such data. The analysis techniques are applied to the data set and data-processing procedure described by Mayhew et al. (1980), a study that treats magnetic anomaly data for Australia and the surrounding ocean obtained by the polar orbit POGO series satellites. It is shown that the data-processing method used by Mayhew et al. is approximately equivalent to an invariant two-dimensional linear filter and that it is reasonably close to optimal with respect to accuracy, although some possible improvements are suggested. However, as is usual when filtering data, some real 'signal' is unavoidably removed along with the 'noise' resulting in errors that can be quite large. A method for reducing these errors by using additional data from a medium inclination orbit satellite (for example, 60 deg inclination) is proposed.

Mcleod, M. G.↗
DOE OSTI2023

Multi-output multilevel best linear unbiased estimators via semidefinite programming

Multifidelity forward uncertainty quantification (UQ) problems often involve multiple quantities of interest and heterogeneous models (e.g., different grids, equations, dimensions, physics, surrogate and reduced-order models). While computational efficiency is key in this context, multi-output strategies in multilevel/multifidelity methods are either sub-optimal or non-existent. In this paper we extend multilevel best linear unbiased estimators (MLBLUE) to multi-output forward UQ problems and we present new semidefinite programming formulations for their optimal setup. Not only do these formulations yield the optimal number of samples required, but also the optimal selection of low-fidelity models to use. While existing MLBLUE approaches are single-output only and require a non-trivial nonlinear optimization procedure, the new multi-output formulations can be solved reliably and efficiently. Here, we demonstrate the efficacy of the new methods and formulations in practical UQ problems with model heterogeneity.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1978

Invariants of optimal minimal-order observer-based compensators

The relations characterizing the optimal minimal-order observer-based compensators for a linear time-invariant multivariable system with a random initial state (or, equivalently, known initial state and white plant-driving noise) have been reported by Miller (1973). In this note we establish in general that the plant transfer function uniquely determines the optimal compensator transfer function, and that this characterizes precisely the degrees of freedom in the compensator design; computational implications of this result are indicated.

Blanvillain, P. J.↗
DOE OSTI2021

Transient Efficiency Flexibility and Reliability Optimization of Coal-Fired Power Plants: Model-Predictive Control Library Development (Report)

This document pertains to the reporting requirements of DOE contract FE-0031767. The document covers the development of a model predictive control (MPC) library for implementing MPC for a general dynamic system. The library is implemented in a standardized manner in Matlab/Simulink, where core functions on model prediction, linearization and formulation and solution of a quadratic programming (QP) optimization problem is done in the core library - independent of the specific application. The user can provide the application-specific dynamic model in continuous and discrete time, to rapidly implement and test the MPC performance in a desktop simulation. The MPC optimization objective and constraints are also easily configured via an Excel file to allow iterative refinement as needed. Finally, the MPC library enables a rapid deployment to a target environment through auto C-code generation and containerization. The MPC library works seamlessly with the model based estimation (MBE) library to obtain the overall output feedback control solution. In this program, the reduced order model (ROM) of a coal-fired power plant (CFPP) is used to implement and test the MPC solution.

01 COAL, LIGNITE, AND PEAT↗
NASA NTRS1979

Linear feature selection with applications

Several ways in which feature selection techniques were used in LACIE are discussed. In all cases, the methods require some a priori information and assumptions; in most, the classification procedure (Bayes optimal) was chosen in advance. The transformations used for dimensionality reduction are linear, that is, the variables in feature space are always linear combinations of the original measurements. Several numerically tractable criteria developed for LACIE, which provide information about the probability of misclassification, are discussed. Recent results on linear feature selection techniques are included. Their use in LACIE is discussed. Related open questions are mentioned.

Decell, H. P., Jr.↗
DOE OSTI2014

An optimal guarding scheme for thermal conductivity measurement using a guarded cut-bar technique, part 1 experimental study

In the guarded cut-bar technique, a guard surrounding the measured sample and reference (meter) bars is temperature controlled to carefully regulate heat losses from the sample and reference bars. Guarding is typically carried out by matching the temperature profiles between the guard and the test stack of sample and meter bars. Problems arise in matching the profiles, especially when the thermal conductivitiesof the meter bars and of the sample differ, as is usually the case. In a previous numerical study, the applied guarding condition (guard temperature profile) was found to be an important factor in measurement accuracy. Different from the linear-matched or isothermal schemes recommended in literature, the optimal guarding condition is dependent on the system geometry and thermal conductivity ratio of sample to meter bar. To validate the numerical results, an experimental study was performed to investigate the resulting error under different guarding conditions using stainless steel 304 as both the sample and meter bars. The optimal guarding condition was further verified on a certified reference material, pyroceram 9606, and 99.95% pure iron whose thermal conductivities are much smaller and much larger, respectively, than that of the stainless steel meter bars. Additionally, measurements are performed using three different inert gases to show the effect of the insulation effective thermal conductivity on measurement error, revealing low conductivity, argon gas, gives the lowest error sensitivity when deviating from the optimal condition. The result of this study provides a general guideline for the specific measurement method and for methods requiring optimal guarding or insulation.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2017

Hydrodynamic Design Optimization and Wave Tank Testing of a Self-Reacting Two-Body Wave Energy Converter

As worldwide energy consumption continues to increase, so does the demand for renewable energy sources. The total available wave energy resource for the United States alone is 2,640 TWh/yr; nearly two thirds of the 4,000 TWh of electricity used in the United States each year. It is estimated that nearly half of that available energy is recoverable through wave energy conversion techniques. In this thesis, a two-body ‘point absorber’ type wave energy converter with a mechanical power-takeoff is investigated. The two-body wave energy converter extracts energy through the relative motion of a floating buoy and a neutrally buoyant submerged body. Using a linear frequency-domain model, analytical solutions of the optimal power and the corresponding power-takeoff components are derived for the two-body wave energy converter. Using these solutions, a case study is conducted to investigate the influence of the submerged body size on the absorbed power of the device in regular and irregular waves. Here it is found that an optimal mass ratio between the submerged body and floating buoy exists where the device will achieve resonance. Furthermore, a case study to investigate the influence of the submerged body shape on the absorbed power is conducted using a time-domain numerical model. Here it is found that the submerged body should be designed to reduce the effects of drag, but to maintain relatively large hydrodynamic added mass and excitation force. To validate the analytical and numerical models, a 1/30th scale model of a two-body wave energy converter is tested in a wave tank. The results of the wave tank tests show that the two-body wave energy converter can absorb nearly twice the energy of a single-body ‘point absorber’ type wave energy converter.

16 TIDAL AND WAVE POWER↗
DOE OSTI2016

Development and clinical evaluation of an ionization chamber array with 3.5 mm pixel pitch for quality assurance in advanced radiotherapy techniques

Purpose: To characterize a new air vented ionization chamber technology, suitable to build detector arrays with small pixel pitch and independence of sensitivity on dose per pulse. Methods: The prototype under test is a linear array of air vented ionization chambers, consisting of 80 pixels with 3.5 mm pixel pitch distance and a sensitive volume of about 4 mm{sup 3}. The detector has been characterized with {sup 60}Co radiation and MV x rays from different linear accelerators (with flattened and unflattened beam qualities). Sensitivity dependence on dose per pulse has been evaluated under MV x rays by changing both the source to detector distance and the beam quality. Bias voltage has been varied in order to evaluate the charge collection efficiency in the most critical conditions. Relative dose profiles have been measured for both flattened and unflattened distributions with different field sizes. The reference detectors were a commercial array of ionization chambers and an amorphous silicon flat panel in direct conversion configuration. Profiles of dose distribution have been measured also with intensity modulated radiation therapy (IMRT), stereotactic radiosurgery (SRS), and volumetric modulated arc therapy (VMAT) patient plans. Comparison has been done with a commercial diode array and with Gafchromic EBT3 films. Results: Repeatability and stability under continuous gamma irradiation are within 0.3%, in spite of low active volume and sensitivity (∼200 pC/Gy). Deviation from linearity is in the range [0.3%, −0.9%] for a dose of at least 20 cGy, while a worsening of linearity is observed below 10 cGy. Charge collection efficiency with 2.67 mGy/pulse is higher than 99%, leading to a ±0.9% sensitivity change in the range 0.09–2.67 mGy/pulse (covering all flattened and unflattened beam qualities). Tissue to phantom ratios show an agreement within 0.6% with the reference detector up to 34 cm depth. For field sizes in the range 2 × 2 to 15 × 15 cm{sup 2}, the output factors are in agreement with a thimble chamber within 2%, while with 25 × 25 cm{sup 2} field size, an underestimation of 4.0% was found. Agreement of field and penumbra width measurements with the flat panel is of the order of 1 mm down to 1 × 1 cm{sup 2} field size. Flatness and symmetry values measured with the 1D array and the reference detectors are comparable, and differences are always smaller than 1%. Angular dependence of the detector, when compared to measurements taken with a cylindrical chamber in the same phantom, is as large as 16%. This includes inhomogeneity and asymmetry of the design, which during plan verification are accounted for by the treatment planning system (TPS). The detector is capable to reproduce the dose distributions of IMRT and VMAT plans with a maximum deviation from TPS of 3.0% in the target region. In the case of VMAT and SRS plans, an average (maximum) deviation of the order of 1% (4%) from films has been measured. Conclusions: The investigated technology appears to be useful both for Linac QA and patient plan verification, especially in treatments with steep dose gradients and nonuniform dose rates such as VMAT and SRS. Major limitations of the present prototype are the linearity at low dose, which can be solved by optimizing the readout electronics, and the underestimation of output factors with large field sizes. The latter problem is presently not completely understood and will require further investigations.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Optimal Design of Food Packaging Considering Waste Management Technologies to Achieve Circular Economy

Plastic packaging plays a fundamental role in the food industry, avoiding food waste and facilitating food access. The increasing plastic production and the lack of appropriate plastic waste management technologies represent a threat to the environmental and human welfare. Therefore, there is an urgent need to identify sustainable packaging solutions. Circular economy (CE) promotes reducing waste and increasing recycling practices to achieve sustainability. In this work, we propose a CE framework based on multi-objective optimization, considering both economic and environmental impacts, to identify optimal packaging designs and waste management technologies. Using mixed-integer linear programming (MILP), techno-economic analysis (TEA), and life cycle assessment (LCA), this work aims to build the first steps in packaging design, informing about the best packaging alternatives and the optimal technology or technologies to process packaging waste. For the economic analysis, we consider the minimum increase in price (MIP) when adding recycling to the cost of each packaging solution, while for the environmental analysis, the greenhouse gas emissions impact was considered. A case study on ground coffee packaging is used to illustrate the proposed framework. The results demonstrate that the multilayer bag option is the most convenient when considering both the chosen economic and environmental impacts.

Life Cycle Analysis↗
DOE OSTI2019

Studies of Front-End Electronics for High-Precision Timing Measurements with LGADs [Poster]

In Time-of-Arrival (ToA) measurements, simulations can be used to optimize precision detection and implementation methods of front-end electronics. The simulation tested in this project takes the response of a filter (in the s-domain) from a noisy input current signal from the detector, an LGAD (Low-Gain Avalanche Diode), and uses a threshold to determine the ToA value for the signal. Measuring the ToA values for a large sample of events and comparing them to a reference statistically produces the timing precision of the simulation. Here, the sub-algorithm to model LGAD events with piecewise linear (PWL) approximations (for more efficient Laplace transforms) was optimized. Using the Fourier Discrete Cosine Transform, 25 points could be selected to describe the primary behavior of the signal. Results showed that timing precision is on par with previous methods. We also found that the new algorithm is faster and equally consistent in producing accurate PWL approximations. Testi ng with larger samples is required to fully verify the new algorithm.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2015

Path optimization by a variational reaction coordinate method. I. Development of formalism and algorithms

The development of algorithms to optimize reaction pathways between reactants and products is an active area of study. Existing algorithms typically describe the path as a discrete series of images (chain of states) which are moved downhill toward the path, using various reparameterization schemes, constraints, or fictitious forces to maintain a uniform description of the reaction path. The Variational Reaction Coordinate (VRC) method is a novel approach that finds the reaction path by minimizing the variational reaction energy (VRE) of Quapp and Bofill. The VRE is the line integral of the gradient norm along a path between reactants and products and minimization of VRE has been shown to yield the steepest descent reaction path. In the VRC method, we represent the reaction path by a linear expansion in a set of continuous basis functions and find the optimized path by minimizing the VRE with respect to the linear expansion coefficients. Improved convergence is obtained by applying constraints to the spacing of the basis functions and coupling the minimization of the VRE to the minimization of one or more points along the path that correspond to intermediates and transition states. The VRC method is demonstrated by optimizing the reaction path for the Müller-Brown surface and by finding a reaction path passing through 5 transition states and 4 intermediates for a 10 atom Lennard-Jones cluster.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1999

A Novel Shape Parameterization Approach

This paper presents a novel parameterization approach for complex shapes suitable for a multidisciplinary design optimization application. The approach consists of two basic concepts: (1) parameterizing the shape perturbations rather than the geometry itself and (2) performing the shape deformation by means of the soft objects animation algorithms used in computer graphics. Because the formulation presented in this paper is independent of grid topology, we can treat computational fluid dynamics and finite element grids in a similar manner. The proposed approach is simple, compact, and efficient. Also, the analytical sensitivity derivatives are easily computed for use in a gradient-based optimization. This algorithm is suitable for low-fidelity (e.g., linear aerodynamics and equivalent laminated plate structures) and high-fidelity analysis tools (e.g., nonlinear computational fluid dynamics and detailed finite element modeling). This paper contains the implementation details of parameterizing for planform, twist, dihedral, thickness, and camber. The results are presented for a multidisciplinary design optimization application consisting of nonlinear computational fluid dynamics, detailed computational structural mechanics, performance, and a simple propulsion module.

Samareh, Jamshid A.↗
DOE OSTI2015

Calibrating transition-metal energy levels and oxygen bands in first-principles calculations: Accurate prediction of redox potentials and charge transfer in lithium transition-metal oxides

Transition-metal (TM) oxides play an increasingly important role in technology today, including applications such as catalysis, solar energy harvesting, and energy storage. In many of these applications, the details of their electronic structure near the Fermi level are critically important for their properties. We propose a first-principles–based computational methodology for the accurate prediction of oxygen charge transfer in TM oxides and lithium TM (Li-TM) oxides. To obtain accurate electronic structures, the Heyd-Scuseria-Ernzerhof (HSE06) hybrid functional is adopted, and the amount of exact Hartree-Fock exchange (mixing parameter) is adjusted to reproduce reference band gaps. We show that the HSE06 functional with optimal mixing parameter yields not only improved electronic densities of states, but also better energetics (Li-intercalation voltages) for LiCoO 2 and LiNiO 2 as compared to the generalized gradient approximation (GGA), Hubbard U corrected GGA (GGA + U), and standard HSE06. We find that the optimal mixing parameters for TM oxides are system specific and correlate with the covalency (ionicity) of the TM species. The strong covalent (ionic) nature of TM-O bonding leads to lower (higher) optimal mixing parameters. We find that optimized HSE06 functionals predict stronger hybridization of the Co 3d and O 2p orbitals as compared to GGA, resulting in a greater contribution from oxygen states to charge compensation upon delithiation in LiCoO 2 . We also find that the band gaps of Li-TM oxides increase linearly with the mixing parameter, enabling the straightforward determination of optimal mixing parameters based on GGA (α = 0.0) and HSE06 (α = 0.25) calculations. Our results also show that G 0 W 0 @ GGA + U band gaps of TM oxides ( M O , M = Mn , Co , Ni ) and LiCoO 2 agree well with experimental references, suggesting that G 0 W 0 calculations can be used as a reference for the calibration of the mixing parameter in cases when no experimental band gap has been reported.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Data-driven modeling and control of dynamical systems using Koopman and Perron-Frobenius operators

This dissertation studies the data-driven modeling and control problem of nonlinear systems by exploiting the linear operator theoretic framework involving Koopman and Perro-Frobenius operator. A systematic linear-operator based controller design procedure has been established, which can be used to solve a variety of nonlinear control problems, including feedback stabilization using control Lyapunov functions, optimal quadratic regulation using Koopman eigenfunctions and convex optimization formulation of optimal control problem using P-F and Koopman operator approximation. As the core of data-driven modeling, we first propose a new algorithm for the finite-dimensional approximation of the linear transfer Koopman and Perron-Frobenius operator from time-series data. We argue that the existing approach for the finite-dimensional approximation of these transfer operators such as Dynamic Mode Decomposition (DMD) and Extended Dynamic Mode Decomposition (EDMD) do not capture two important properties of these operators, namely positivity and Markov property. The algorithm we propose preserves these two properties. We call the proposed algorithm as naturally structured DMD (NSDMD) since it retains the inherent properties of these operators. Naturally structured DMD algorithm leads to a better approximation of the steady-state dynamics of the system regarding computing Koopman and Perron- Frobenius operator eigenfunctions and eigenvalues. However, preserving positivity property is critical for capturing the real transient dynamics of the system. This positivity property of the transfer operators and it's finite-dimensional approximation play an important role for controller and estimator design of nonlinear systems. To solve the feedback stabilization problem for nonlinear control systems, we tried to take advantage of the Koopman operator framework. The Koopman operator approach provides a linear representation for a nonlinear dynamical system and a bilinear representation for a nonlinear control system. The problem of feedback stabilization of a nonlinear control system is then transformed to the stabilization of a bilinear control system. We propose a control Lyapunov function (CLF)-based approach for the design of stabilizing feedback controllers for the bilinear system. The search for finding a CLF for the bilinear control system is formulated as a convex optimization problem. This leads to a schematic procedure for designing CLF-based stabilizing feedback controllers for the bilinear system and hence the original nonlinear system. Another advantage of the proposed controller design approach outlined in this dissertation is that it does not require explicit knowledge of system dynamics. In particular, the bilinear representation of a nonlinear control system in the Koopman eigenfunction space can be obtained from time-series data. Next, we study the optimal quadratic regulation problem for nonlinear systems. The linear operator theoretic framework involving the Koopman operator is used to lift the dynamics of nonlinear control system to an infinite-dimensional bilinear system. The optimal quadratic regulation problem for nonlinear system is formulated in terms of the finite-dimensional approximation of the bilinear system. A convex optimization-based approach is proposed for solving the quadratic regulator problem for bilinear system. We applied a variety of examples and compared the simulation results between our framework and conventional LQR control using linearized model. For more general optimal control problems, we provide a density-function based convex formulation for the optimal control problem of the nonlinear system. The convex formulation relies on the duality result in the stability theory of a dynamical system involving density function and Perron-Frobenius operator. The optimal control problem is formulated as an infinite-dimensional convex optimization program. The finite-dimensional approximation of the optimization problem relies on the recent advances made in the data-driven computation of the Koopman operator, which is dual to the Perron-Frobenius operator. Simulation results are presented to demonstrate the application of the developed framework.

Huang, Bowen↗
DOE OSTI2023

Learning Provably Stable Local Volt/Var Controllers for Efficient Network Operation

Here this paper develops a data-driven framework to synthesize local Volt/Var control strategies for distributed energy resources (DERs) in power distribution grids (DGs). Aiming to improve DG operational efficiency, as quantified by a generic optimal reactive power flow (ORPF) problem, we propose a two-stage approach. The first stage involves learning the manifold of optimal operating points determined by an ORPF instance. To synthesize local Volt/Var controllers, the learning task is partitioned into learning local surrogates (one per DER) of the optimal manifold with voltage input and reactive power output. Since these surrogates characterize efficient DG operating points, in the second stage, we develop local control schemes that steer the DG to these operating points. We identify the conditions on the surrogates and control parameters to ensure that the locally acting controllers collectively converge, in a global asymptotic sense, to a DG operating point agreeing with the local surrogates. We use neural networks to model the surrogates and enforce the identified conditions in the training phase. AC power flow simulations on the IEEE 37-bus network empirically bolster the theoretical stability guarantees obtained under linearized power flow assumptions. The tests further highlight the optimality improvement compared to prevalent benchmark methods.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Automated control and optimization of laser-driven ion acceleration

The interaction of relativistically intense lasers with opaque targets represents a highly non-linear, multi-dimensional parameter space. This limits the utility of sequential 1D scanning of experimental parameters for the optimization of secondary radiation, although to-date this has been the accepted methodology due to low data acquisition rates. High repetition-rate (HRR) lasers augmented by machine learning present a valuable opportunity for efficient source optimization. Here, an automated, HRR-compatible system produced high-fidelity parameter scans, revealing the influence of laser intensity on target pre-heating and proton generation. A closed-loop Bayesian optimization of maximum proton energy, through control of the laser wavefront and target position, produced proton beams with equivalent maximum energy to manually optimized laser pulses but using only 60% of the laser energy. This demonstration of automated optimization of laser-driven proton beams is a crucial step towards deeper physical insight and the construction of future radiation sources.

47 OTHER INSTRUMENTATION↗