Radiance | EPFL Graph Search

In radiometry, radiance is the radiant flux emitted, reflected, transmitted or received by a given surface, per unit solid angle per unit projected area. Radiance is used to characterize diffuse emission and reflection of electromagnetic radiation, and to quantify emission of neutrinos and other particles. The SI unit of radiance is the watt per steradian per square metre (). It is a directional quantity: the radiance of a surface depends on the direction from which it is being observed. The related quantity spectral radiance is the radiance of a surface per unit frequency or wavelength, depending on whether the spectrum is taken as a function of frequency or of wavelength. Historically, radiance was called "intensity" and spectral radiance was called "specific intensity". Many fields still use this nomenclature. It is especially dominant in heat transfer, astrophysics and astronomy. "Intensity" has many other meanings in physics, with the most common being power per unit area.

Determination of the radiance of cylindrical light diffusers: design of a one-axis charge-coupled device camera-based goniometer setup

Jenny Bertholet, Blaise Lovisa, Andreas Pitzschke, Georges Wagnières, Matthieu Zellweger

A one-axis charge-coupled device camera-based goniometer setup was developed to measure the three-dimensional radiance profile ( longitudinal, azimuthal, and polar) of cylindrical light diffusers in air and water. An algorithm was programmed to project the two-dimensional camera data onto the diffuser coordinates. The optical system was designed to achieve a spatial resolution on the diffuser surface in the submillimeter range. The detection threshold of the detector was well below the values of measured radiance. The radiance profiles of an exemplary cylindrical diffuser measured in air showed local deviations in radiance below 10% for wavelengths at 635 and 671 nm. At 808 nm, deviations in radiance became larger, up to 45%, most probable due to the manufacturing process of the diffuser. Radiance profiles measured in water were less Lambertian than in air due to the refractive index matching privileging the radial decoupling of photons from the optical fiber. (C) 2017 Society of Photo-Optical Instrumentation Engineers (SPIE)

Spie-Soc Photo-Optical Instrumentation Engineers2017

Simulation and Optimization of Heliostat Fields using Radiance and MOO fot the Design of a 300 MWth Central Receiver

Germain Augsburger

This work discusses solar power towers and especially the simulation and optimization of heliostat fields. The technological stateof the art is given through typical characteristic values and dimensions of some existing central tower power plants such as th so-called Solar Two in California and the PS10 in Spain. Leaving cycle losses aside, the field losses involved are described and roughly estimated thanks to commonly measured and computed values, typically coming to an 80% overall field efficiency. On the other side, the coats that must be taken into consideration when designing a heliostat field are listed and approached through correlations, giving for instance a total investment cost of $15 million for relatively large fields ( approximately 700 [m]). The raytracing software Radiance is then chosen for modeling an entire heliostat field with a central receiver, and thus for running simulations over time for different sun positions. Some given field layouts such as those obtained in published cases can be visualized and heat flux at the receiver‘s surface is computed thanks to Radiance tools before being displayed through a MATLAB post-processing. For validating Radiance calculations, the results are first compared with published cases: the receiver‘s total thermal energy produced over a year is generally between 5 and 10 [%] lower than these published results. Secondly, the Radiance heat flux profile has to be compared with some published experimental results: based on measurements led at the PSA Solar de Almeria). the heat flux profile (gradient) is close to measurements, but computed and measured total thermal powers do not match when computed and measured peak values do match. Therefore the Radiance heat flux still requires further validation probably involving some model adjustments. Nevertheless, this does not prevent from implementing some very large fields (more than 3000 heliostats) optimized with the MOO multi-objective optimizer after having modified routines for generating surrounding fields. and thus resulting in a first overview of what the heat flux profile on a cylindrical receiver may look like for a total thermal power of 300 [M Wth].

2008

Differentiable inverse rendering based on radiative backpropagation

Wenzel Alban Jakob, Merlin Eléazar Nimier-David

A computer-implemented inverse rendering method is provided. The method comprises: computing an adjoint image by differentiating an objective function that evaluates the quality of a rendered image, image elements of the adjoint image encoding the sensitivity of spatially corresponding image elements of the rendered image with respect to the objective function; sampling the adjoint image at a respective sample position to determine a respective adjoint radiance value associated with the respective sample position; emitting the respective adjoint radiance value into a scene model characterised by scene parameters; determining an interaction location of a respective incident adjoint radiance value with a surface and/or volume of the scene model; determining a respective incident radiance value or an approximation thereof at the interaction location, the respective incident radiance value expressing the amount of incident radiance that travels from the surrounding environment towards the interaction location; and updating a scene parameter gradient by using at least the interaction location and the respective incident adjoint radiance value and the respective incident radiance value or its approximation at the interaction location.

2021

Simulation and Optimization of Heliostat Fields using Radiance and MOO fot the Design of a 300 MWth Central Receiver

Germain Augsburger

2008