arXiv subjects

Jeffery R. Roesler

Publications and source records attributed to Jeffery R. Roesler.

4 recordsLinked to original sources

arXiv2026

Fracture under body forces: An accessible test and analysis

Fracture in large-scale structures --- from failing concrete dams to calving glaciers --- is dominated by self-weight. Yet, owing to their immense scale, directly studying when and where cracks nucleate and propagate in these systems under gravity is unfeasible. To date, experimental investigations have largely relied on mimicking self-weight in scaled-down specimens via centrifugal forces, necessitating specialized centrifuge facilities. In this Letter, we introduce a simple benchtop test that bypasses the need for this infrastructure. The method utilizes a cantilever beam containing a downward-pointing V-notch, loaded solely by its self-weight. Through appropriate selection of the notch geometry and placement and the beam dimensions, the setup forces a crack to nucleate at the notch tip and propagate through the specimen in a measurable manner. We demonstrate the utility of this self-weight fracture test on a 3D-printable mortar and analyze the results using the fracture theory recently introduced in (\citeauthor{LPKFG2026}, 2026). \emph{Inter alia}, the findings provide a first validation of the theory for fracture driven by body forces.

cond-mat.other↗

arXiv2026

A Guide to Fully Characterize the Fracture Properties of Cementitious Materials from Simple Experiments

Guided by recent advances in the understanding of nucleation and propagation of fracture in elastic brittle materials, this paper proposes a suite of three simple experiments that permit the measurement of the three macroscopic material properties governing when and where cracks nucleate and propagate in structures made of cementitious materials that are subjected to arbitrary monotonic quasi-static loading conditions. The first experiment is that of the uniaxial compression of a cylindrical specimen, which enables the extraction of the elastic properties -- namely, the Young's modulus and Poisson's ratio -- as well as the uniaxial compressive strength. The second experiment is the Brazilian fracture test, performed with flat platens on a material disk to determine the uniaxial tensile strength. Having knowledge of the uniaxial compressive and uniaxial tensile strengths then allows for the estimation of the strength surface of the material via interpolation (e.g., a Drucker-Prager fit). Finally, the third experiment is the wedge split test on a notched cube, which yields the fracture toughness. We demonstrate by means of direct comparisons with four-point and three-point bending tests on both unnotched and notched beams made of a 3D-printable mortar mixture that the elasticity, strength, and toughness properties obtained from the proposed tests are sufficient to predict the nucleation and propagation of fracture for any structure (granted separation of length scales) made of cementitious materials under any monotonic quasi-static loading condition.

cond-mat.soft↗

arXiv2026

Breaking Four-Point and Three-Point Bending Tests

Since their initial standardizations in the 1930s and 1950s, the so-called four-point and three-point bending tests on unnotched beams have been embraced by practitioners as two popular methods to indirectly measure the tensile strength of concrete, ceramics, and other materials with a large compressive strength relative to their tensile strength. This is because of the ease that the tests afford in both the preparation of the specimen (a beam of rectangular cross section) and the application of the loads (simple supports pressing on the specimen). Yet, this practical advantage has to be tempered by the fact that the observations from both of these tests -- being \emph{indirect} experiments in the sense that they involve \emph{not} uniform uniaxial tension but non-uniform triaxial stress states throughout the specimen -- have to be appropriately interpreted to be useful. By making use of the phase-field fracture theory initiated by Kumar, Francfort, and Lopez-Pamies (2018), which has been recently established as a complete theory of fracture capable of accurately describing the nucleation and propagation of cracks in elastic brittle materials under arbitrary quasistatic loading conditions, the main objective of this paper is to carry out a thorough 3D quantitative analysis of when and where fracture nucleates and propagates in four-point and three-point bending tests and thereby establish how to appropriately interpret their results. As a corollary, the analysis provides an explanation for why four-point bending tests typically yield smaller flexural strengths than three-point bending tests, a source of constant headaches for practitioners who have been left to wonder which test -- if any -- would be more appropriate for their purposes.

cond-mat.mtrl-sci↗

arXiv2020

Automatic joint damage quantification using computer vision and deep learning

Joint raveled or spalled damage (henceforth called joint damage) can affect the safety and long-term performance of concrete pavements. It is important to assess and quantify the joint damage over time to assist in building action plans for maintenance, predicting maintenance costs, and maximize the concrete pavement service life. A framework for the accurate, autonomous, and rapid quantification of joint damage with a low-cost camera is proposed using a computer vision technique with a deep learning (DL) algorithm. The DL model is employed to train 263 images of sawcuts with joint damage. The trained DL model is used for pixel-wise color-masking joint damage in a series of query 2D images, which are used to reconstruct a 3D image using open-source structure from motion algorithm. Another damage quantification algorithm using a color threshold is applied to detect and compute the surface area of the damage in the 3D reconstructed image. The effectiveness of the framework was validated through inspecting joint damage at four transverse contraction joints in Illinois, USA, including three acceptable joints and one unacceptable joint by visual inspection. The results show the framework achieves 76% recall and 10% error.

cs.CV↗