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Related work
Laboratory Study:
Combining Signal Features of Ground-Penetrating Radar to Classify Moisture Damage in Layered Building Floors
https://doi.org/10.3390/app11198820
On-Site Study:
TBA
Doctoral Thesis:
Non-destructive classification of moisture deterioration in layered building floors using ground penetrating radar
https://doi.org/10.14279/depositonce-19306
Measurement Parameters
The GPR measurements were carried out with the SIR 20 from GSSI and a 2 GHz antenna pair (bandwidth 1 GHz to 3 GHz) in common-offset configuration. Each B-Scan consists of N A-Scans, each including 512 samples of a 11 ns time window. Survey lines were recorded with 250 A-Scans/ meter, which equals a 4 mm spacing between each A-Scan No Gains were applied.
Folder Description:
Lab_dry, Lab_insulDamage, Lab_screedDamage
- each contain 168 Measurements (B-Scans) in .csv on 84 dry floors, floors with insulation damage and screed damage.
- each floor setup was measured twice on two orthogonal survey lines, indicated by _Line1_ and _Line2_ in the file name.
- the file names encode the building floor setup e.g. CT50XP100 describes a 50 mm cement screed with 100 mm extruded polystyrene below
- the material codes are
CT: cement screed, CA: anhydrite screed, EP: expanded polystyrene, XP: extruded polystyrene, GW: glass wool, PS: perlites
further information can be found in the publication https://doi.org/10.3390/app11198820
OnSite_
- 5 folders containing B-Scans on 5 different practical moisture damages
- the building floor setup is encoded according to the lab with an additional measurement point numbering at the start and a damage case annotation at the end of the file name with _dry, _insulationDamage and_screedDamage
File Description:
B-Scans, Measurement files - no header
- dimension: 512 x N data point with N beeing the number of A-Scans including 512 samples of a 11 ns time window.
- survey lines were recorded with 250 A-Scans/ meter, which equals a 4 mm spacing between each A-Scan
Moisture References
- Moist_Reference of On-Site Locations include the columns MeasPoint: Measurement point, wt%Screed: moisture content of screed layer in mass percent; wt%Insul: moisture content of insulation layer in mass percent. References were obtained by drilling cores with 68 mm diameter in the center of each survey line.
- Moist_Reference_Screed of Lab data include the columns Screed: Screed material and thickness in mm, wt%Screed moisture content of screed layer in mass percent
- Moist Reference_Insul of Lab data include the columns Insulation: Insulation material and thickness in mm, water addition in l: water added to the insulation layer in liters, V%Insulation: water added to the insulation layer in volume percent, RH%: resulting relative humidy in the insulation layer during measurement. These References are only avaible for Lab measurements on insulation damages.
In construction and demolition waste (CDW) recycling, the preference to date has been to apply simple but proven techniques to sort and process large quantities of construction rubble in a short time. This contrasts with the increasingly complex composite materials and structures in the mineral building materials industry. An automated, sensor-based sorting of these building materials could complement or replace the practice of manual sorting to improve processing speed, recycling rates, sorting quality, and prevailing health conditions for the executing staff.
A joint project of partners from industry and research institutions approaches this task by investigating and testing the combination of laser-induced breakdown spectroscopy (LIBS) with near-infrared (NIR) spectroscopy and visual imaging. Joint processing of information (data fusion) is expected to significantly improve the sorting quality of CDW, and may enable the detection and separation of impurities such as SO3-cotaining building materials (gypsum, aerated concrete, etc.)
We present current advances and results about the methodological development combining LIBS with NIR spectroscopy and visual imaging. Here, applying data fusion proves itself beneficial to improve recognition rates. In the future, a laboratory prototype will serve as a fully automated measurement setup to allow real-time classification of CDW on a conveyor belt.
Laser-based active thermography is a contactless non-destructive testing method to detect material defects by heating the object and measuring its temperature increase with an infrared camera. Systematic deviations from predicted behavior provide insight into the inner structure of the object. However, its resolution in resolving internal structures is limited due to the diffusive nature of heat diffusion. Thermographic super resolution (SR) methods aim to overcome this limitation by combining multiple thermographic measurements and mathematical optimization algorithms to improve the defect reconstruction.
Thermographic SR reconstruction methods involve measuring the temperature change in an object under test (OuT) heated with multiple different spatially structured illuminations. Subsequently, these measurements are inputted into a severely ill-posed and heavily regularized inverse problem, producing a sparse map of the OuT’s internal defect structure. Solving this inverse problem relies on limited priors, such as defect-sparsity, and iterative numerical minimization techniques. Previously mostly experimentally limited to one-dimensional regions of interest (ROIs), this thesis aims to extend the method to the reconstruction of two-dimensionalROIs with arbitrary defect distributions while maintaining reasonable experimental complexity. Ultimately, the goal of this thesis is to make the method suitable for a technology transfer to industrial applications by advancing its technology readiness level (TRL).
In order to achieve the aforementioned goal, this thesis discusses the numerical expansion of a thermographic SR reconstruction method and introduces two novel algorithms to invert the underlying inverse problem. Furthermore, a forward solution to the inverse problem in terms of the applied SR reconstruction model is set up. In conjunction with an additionally proposed algorithm for the automated determination of a set of (optimal) regularization parameters, both create the possibility to conduct analytical simulations to characterize the influence of the experimental parameters on the achievable reconstruction quality. On the experimental side, the method is upgraded to deal with two-dimensional ROIs, and multiple measurement campaigns are performed to validate the proposed inversion algorithms, forward solution and two exemplary analytical studies. For the experimental implementation of the method, the use of a laser-coupled DLP-projector is introduced, which allows projecting binary pixel
patterns that cover the whole ROI, reducing the number of necessary measurements per ROI significantly (up to 20x).
Finally, the achieved reconstruction of the internal defect structure of a purpose-made OuT is qualitatively and qualitatively benchmarked against well-established thermographic testing methods based on homogeneous illumination of the ROI. Here, the background-noise-free two-dimensional photothermal SR reconstruction results show to outclass all defect reconstructions by the considered reference methods.
Asphalt is one of the most common materials used in road construction. It is subject to both chemical and structural aging processes during use. At least to our knowledge, it is not currently known whether these aging processes also lead to a measurable change in the thermal properties of asphalt. If so, these changes could be exploited for non-destructive testing of the aging condition in situ. Photothermal analysis of a component surface involves looking at the time course of the surface temperature during and after pulse-like heating with an expanded laser beam. In the case of concrete surfaces, this method works well under laboratory conditions. It allowed the determination of the thermal effusivity. Now it should be investigated whether the photothermal signal allows conclusions to be made regarding the aging state of the asphalt. Within the scope of this paper, 2 asphalt specimens were investigated: a closed asphalt with 3% void content (SMA 11S) and an open-pore asphalt with 25% void content (PA 8). Both samples were artificially degraded according to a standardized procedure, leaving a portion of the surface unaffected. Subsections from both areas were then separated for photothermal testing. It was found, that the photothermal method is apparently not sensitive enough to detect aging on asphalt in general. However, it is noteworthy that both asphalt types heat up significantly faster than would be expected from the theory of heat conduction, which might be explained by the specific microstructure.
Geschlossene Materialkreisläufe und sortenreine Materialfraktionen sind erforderlich, um hohe Verwertungs und Recyclingquoten in der Bauindustrie zu erreichen Beim Recycling von Bau und Abbruchabfällen wurden bisher bevorzugt einfache, aber bewährte Techniken eingesetzt, um große Mengen Bauschutt in kurzer Zeit zu verarbeiten Dies steht im Gegensatz zu den immer komplexer werdenden Verbundwerkstoffen in der Mineralbaustoffindustrie Die aktuell oft praktizierte händische Klaubung bürgt viele Risiken und Gefahren für das ausführende Personal und basiert lediglich auf offensichtlichen, visuell erkennbaren Unterschieden zur Trennung Eine automatisierte, sensorgestützte Sortierung dieser Baustoffe könnte diese Praxis ergänzen oder ersetzen, um die Verarbeitungsgeschwindigkeit, die Recyclingraten, die Sortierqualität und die vorherrschenden Gesundheitsbedingungen zu verbessern.
Geschlossene Materialkreisläufe und sortenreine Materialfraktionen sind erforderlich, um hohe Verwertungs und Recyclingquoten in der Bauindustrie zu erreichen Beim Recycling von Bau und Abbruchabfällen wurden bisher bevorzugt einfache, aber bewährte Techniken eingesetzt, um große Mengen Bauschutt in kurzer Zeit zu verarbeiten Dies steht im Gegensatz zu den immer komplexer werdenden Verbundwerkstoffen in der Mineralbaustoffindustrie Die aktuell oft praktizierte händische Klaubung bürgt viele Risiken und Gefahren für das ausführende Personal und basiert lediglich auf offensichtlichen, visuell erkennbaren Unterschieden zur Trennung Eine automatisierte, sensorgestützte Sortierung dieser Baustoffe könnte diese Praxis ergänzen oder ersetzen, um die Verarbeitungsgeschwindigkeit, die Recyclingraten, die Sortierqualität und die vorherrschenden Gesundheitsbedingungen zu verbessern.
Laser-based active thermography is a contactless non-destructive testing method to detect material defects by heating the object and measuring its temperature increase with an infrared camera. Systematic deviations from predicted behavior provide insight into the inner structure of the object. However, its resolution in resolving internal structures is limited due to the diffusive nature of heat diffusion. Thermographic super resolution (SR) methods aim to overcome this limitation by combining multiple thermographic measurements and mathematical optimization algorithms to improve the defect reconstruction.
Thermographic SR reconstruction methods involve measuring the temperature change in an object under test (OuT) heated with multiple different spatially structured illuminations. Subsequently, these measurements are inputted into a severely ill-posed and heavily regularized inverse problem, producing a sparse map of the OuT’s internal defect structure. Solving this inverse problem relies on limited priors, such as defect-sparsity, and iterative numerical minimization techniques. Previously mostly experimentally limited to one-dimensional regions of interest (ROIs), this thesis aims to extend the method to the reconstruction of twodimensional ROIs with arbitrary defect distributions while maintaining reasonable experimental complexity. Ultimately, the goal of this thesis is to make the method suitable for a technology transfer to industrial applications by advancing its technology readiness level (TRL).
In order to achieve the aforementioned goal, this thesis discusses the numerical expansion of a thermographic SR reconstruction method and introduces two novel algorithms to invert the underlying inverse problem. Furthermore, a forward solution to the inverse problem in terms of the applied SR reconstruction model is set up. In conjunction with an additionally proposed
algorithm for the automated determination of a set of (optimal) regularization parameters, both create the possibility to conduct analytical simulations to characterize the influence of the experimental parameters on the achievable reconstruction quality. On the experimental side, the method is upgraded to deal with two-dimensional ROIs, and multiple measurement campaigns are performed to validate the proposed inversion algorithms, forward solution
and two exemplary analytical studies. For the experimental implementation of the method, the use of a laser-coupled DLP-projector is introduced, which allows projecting binary pixel patterns that cover the whole ROI, reducing the number of necessary measurements per ROI significantly (up to 20x).
Finally, the achieved reconstruction of the internal defect structure of a purpose-made OuT is qualitatively and qualitatively benchmarked against well-established thermographic testing methods based on homogeneous illumination of the ROI. Here, the background-noise-free twodimensional photothermal SR reconstruction results show to outclass all defect reconstructions by the considered reference methods.
The capability to produce complexly and individually shaped metallic parts is one of the main advantages of the laser powder bed fusion (PBF LB/M) process. Development of material and machine specific process parameters is commonly based on results acquired from small cubic test coupons of about 10 mm edge length. Such cubes are usually used to conduct an optimization of process parameters to produce dense material. The parameters are then taken as the basis for the manufacturing of real part geometries. However, complex geometries go along with complex thermal histories during the manufacturing process, which can significantly differ from thermal conditions prevalent during the production of simply shaped test coupons. This may lead to unexpected and unpredicted local inhomogeneities of the microstructure and defect distribution in the final part and it is a root cause of reservations against the use of additive manufacturing for the production of safety relevant parts. In this study, the influence of changing thermal conditions on the resulting melt pool depth of 316L stainless steel specimens is demonstrated. A variation of thermo-graphically measured intrinsic preheating temperatures was triggered by an alteration of inter layer times and a variation of cross section areas of specimens for three distinct sets of process parameters. Correlations between the preheating temperature, the melt pool depth, and occurring defects were analyzed. The limited expressiveness of the results of small density cubes is revealed throughout the systematic investigation. Finally, a clear recommendation to consider thermal conditions in future process parameter optimizations is given.
For the wide acceptance of the use of additive manufacturing (AM), it is required to provide reliable testing methods to ensure the safety of the additively manufactured parts. A possible solution could be the deployment of in-situ monitoring during the build process. However, for laser powder bed fusion using metal powders (PBF-LB/M ) only a few in-situ monitoring techniques are commercially available (optical tomography, melt pool monitoring) but not researched to an extent that allows to guarantee the adherence to strict quality and safety standards.
In this contribution, we present results of a study of PBF-LB/M printed parts made of the nickel-based superalloy Haynes 282. The formation of defects was provoked by local variations of the process parameters and monitored by thermography, optical tomography and melt pool monitoring. Afterwards, the defects were characterized by computed tomography (CT) to identify the detection limits of the used in-situ techniques.
The global demand for concrete is growing, and with it, its carbon footprint. Current literature proposes biochar, a product of pyrolysis, as a possible car-bon sink to reduce the carbon footprint of concrete. This work investigates the microstructure of Portland cement pastes with 0%, 5%, and 25% of the cement replaced with wood biochar, since this should influence its macro-scopic mechanical properties. MIP, gas sorption, NMR, and µ-CT were used to analyze the pore space of the three materials. The combination of these methods, each with different resolution, enables a multi-scale investigation of biochar impact on the microstructure of cement pastes. NMR confirmed that biochar can absorb moisture and, thus, reduces the effective water-to-cement ratio. MIP and gas sorption results show 0% and 5% volume re-placement have similar gel pore structure. The results from µ-CT investiga-tions suggest that biochar may reduce the formation of larger pores. The in-clusion of non-reactive porous particles such as biochar increase the porosity of the material and should act as a weakness in terms of mechanical proper-ties. Overall, this study highlights the need to carefully tailor replacement rates to control the impact of biochar on the microstructure concrete mixtures and sees a strong need for further studies on mechanical properties.