Compass Measurements Research Articles

Complex landslides: discrepancy between varied partial movement mechanisms detected in crevice-type caves and by formal investigation

Mass movements can be investigated usually only from the surface or, more in-depth, indirectly by geophysical methods and by spot drilling. Crevice-type caves allow us to visit and observe the inner environment of the slope deformations. Such caves are typically composed of systems comprising long and high joint-predisposed corridors, enabling us to investigate geological outcrops hundreds of meters long and tens of meters deep within the landslide mass. The present paper shows the diversity of particular gravitational movements influencing the vast slid rock blocks, which seem to remain intact and consolidated within the landslide body. By use of geological compass measurement and statistical evaluation, we detect complex movement mechanisms in most investigated cases, often without any impact on the topography above. The results prove the existence of a great difference between the overall behavior of the deformation and its individual rock blocks, as well as discrepancy between movement mechanisms detected in crevice-type caves and by formal investigation. Furthermore, this paper discusses the related horizontal rotation and subsidence movements documented by previous studies. We can conclude that most deformations are complex.

Transverse single spin asymmetry AUTsin(ϕh−ϕS) for single hadron production in semi-inclusive DIS

In this paper, we study the single spin asymmetry ${A}_{UT}^{\mathrm{sin}({\ensuremath{\phi}}_{h}\ensuremath{-}{\ensuremath{\phi}}_{S})}$ of a single hadron production in semi-inclusive deep inelastic scattering within the framework of transverse momentum dependent factorization up to the next-to-leading logarithmic order of QCD. The asymmetry is a contribution of the convolution of the Sivers function and the unpolarized fragmentation function. Specifically, the Sivers function in the coordinate space and perturbative region can represent the convolution of the $C$ coefficients and the corresponding collinear correlation functions, among which the Qiu-Sterman function is the most relevant one. We perform a detailed phenomenological analysis of the Sivers asymmetry at the kinematics of the HERMES and the COMPASS measurements. It is found that the obtained ${x}_{B}$-, ${z}_{h}$-, and ${P}_{h\ensuremath{\perp}}$-dependent asymmetries are basically consistent with the HERMES and the COMPASS measurements.

Non-planarity, scale-dependent roughness and kinematic properties of the Pidima active normal fault scarp (Messinia, Greece) using high-resolution terrestrial LiDAR data

Terrestrial LiDAR (TLS), photogrammetric and field data were collected during the years 2014, 2015 and 2017, at a 20-m long limestone scarp locality along the N–S striking, 70° west-dipping, active Pidima fault (Messinia, SW Peloponnese, Greece). This locality presents an artificially exhumed portion of an active fault plane, thus providing a unique opportunity to study kinematics and limestone scarp morphology (including its curvature and roughness). The survey of 2015 offered a high-density point cloud of the fault scarp with 6-mm working resolution, creating a very close to real life representation 3D model. We found that scarp geometry is non-planar with increasing convexity up-dip and increasing northwesterly dip-directions from north towards south, along strike. Non-planarity is also recorded from the morphological data along strike with the appearance of several, slip-parallel troughs and ridges with a mean distance (half-wavelength) of 0.75 m. The fault-plane roughness (absolute values) is scale dependent. The roughness configuration attains a slip-parallel pattern for observation scales above 1-cm. At observations scales less than 1-cm a slip-normal pattern is weakly visible. The obtained TLS results agree with field data (manual compass measurements) and macroscopic observations. We infer an earthquake magnitude of 6.2 ± 0.2 for the last event along the Pidima fault based on the measured thickness of the smooth stripe that was imaged by t-LiDAR along the non-exhumed surface of the scarp.

Sin(2ϕ−ϕS) azimuthal asymmetry in the pion induced Drell-Yan process within TMD factorization

We investigate the single transverse-spin asymmetry with a $\sin (2\phi-\phi_S)$ modulation in the pion-induced Drell-Yan process within the theoretical framework of the transverse momentum dependent factorization. The asymmetry is contributed by the convolution of the Boer-Mulders function and the transversity. We adopt the model results for the distributions of the pion meson from the light-cone wavefunction approach and the available parametrization for the distributions of the proton to numerically estimate the $\sin (2\phi-\phi_S)$ asymmetry in $\pi^- p$ Drell-Yan at the kinematics of the COMPASS at CERN. To implement the TMD evolution formalism of parton distribution functions, we apply the recently extracted nonperturbative Sudakov form factor associated with the distribution functions of the proton and the pion. It is found that our prediction on the single transverse-spin dependent asymmetry ${\sin (2\phi-\phi_S)}$ as functions of $x_p$, $x_\pi$, $x_F$ and $q_\perp$ is qualitatively consistent with the recent COMPASS measurement in both sign and magnitude.

Dispersion relations for hadronic light-by-light and the muon g − 2

The largest uncertainties in the Standard Model calculation of the anomalous magnetic moment of the muon (g−2)µ come from hadronic effects, namely hadronic vacuum polarization (HVP) and hadronic lightby-light (HLbL) contributions. Especially the latter is emerging as a potential roadblock for a more accurate determination of (g−2)µ. The main focus here is on a novel dispersive description of the HLbL tensor, which is based on unitarity, analyticity, crossing symmetry, and gauge invariance. This opens up the possibility of a data-driven determination of the HLbL contribution to (g−2)µ with the aim of reducing model dependence and achieving a reliable error estimate. Our dispersive approach defines unambiguously the pion-pole and the pion-box contribution to the HLbL tensor. Using Mandelstam double-spectral representation, we have proven that the pion-box contribution coincides exactly with the one-loop scalar-QED amplitude, multiplied by the appropriate pion vector form factors. Using dispersive fits to high-statistics data for the pion vector form factor, we obtain $ \alpha _\mu ^{\pi {\rm{ - box}}} = - 15.9(2) \times {10^{ - 11}} $. A first model-independent calculation of effects of ππ intermediate states that go beyond the scalar-QED pion loop is also presented. We combine our dispersive description of the HLbL tensor with a partial-wave expansion and demonstrate that the known scalar-QED result is recovered after partial-wave resummation. After constructing suitable input for the γ*γ* → ππ helicity partial waves based on a pion-pole left-hand cut (LHC), we find that for the dominant charged-pion contribution this representation is consistent with the two-loop chiral prediction and the COMPASS measurement for the pion polarizability. This allows us to reliably estimate S-wave rescattering effects to the full pion box and leads to $ \alpha _\mu ^{\pi {\rm{ - box}}} + \alpha _{\mu ,J = 0}^{\pi \pi ,\pi {\rm{ - pole}}\,{\rm{LHC}}} = - 24(1) \times {10^{ - 11}} $.

COMPASS measurement of hard exclusive π0 muoproduction cross-section

One of the goals of the COMPASS experimental program is the measurement of exclusive processes. The exclusive processes, such as Deep Virtual Compton Scattering (DVCS) or Hard Exclusive Meson Production, are important inputs for constraining the General Parton Distributions (GPDs). Exclusive π0 production is the main source of background for DVCS process, while it provides important information on chiral-odd GPDs. The dedicated GPD program started with a one month pilot run in 2012, followed by two full years of data taking in 2016-2017, using 160 GeV/c positive and negative muon beams, a liquid hydrogen target and new detectors such as a recoil proton detector and a large-angle electromagnetic calorimeter. Our results of the exclusive π0 production from the 2012 pilot run, recently submitted to publication, are presented. Using average of both μ+ and μ− data, the γ*p cross section is extracted as a function of the squared four-momentum transfer t, and of the azimuthal angle ϕ between the scattering plane and the π0 production plane. The average kinematics of the measurement are ⟨Q2⟩ = 2.0 (GeV/c)2, ⟨ν⟩ = 12.8 GeV, ⟨xB⟩ = 0.093, and ⟨−t⟩ = 0.256 (GeV/c)2. A comparison of our results with the phenomenological Goloskokov-Kroll model are shown. Prospect are given on upcoming results of the 2016/17 measurement.

3D HAZARD ANALYSIS AND OBJECT-BASED CHARACTERIZATION OF LANDSLIDE MOTION MECHANISM USING UAV IMAGERY

Abstract. Late years, innovative close-range remote sensing technology such as Unmanned Aerial Vehicle (UAV) photogrammetry and Terrestrial Laser Scanning (TLS) are widely applied in the field of geoscience due to their efficiency in collecting data about surface morphology. Their main advantage stands on the fact that conventional methods are mainly collecting point measurements such as compass measurements of bedding and fracture orientation solely from accessible areas. The current research aims to demonstrate the applicability of UAVs in managing landslide and rockfall hazard in mountainous environments during emergency situations using object-based approach. Specifically, a detailed UAV survey took place in a test site namely as Proussos, one of the most visited and famous Monasteries in the territory of Evritania prefecture, in central Greece. An unstable steep slope across the sole road network results in continuous failures and road cuts after heavy rainfall events. Structure from Motion (SfM) photogrammetry is used to provide detailed 3D point clouds describing the surface morphology of landslide objects. The latter resulted from an object-based classification approach of the photogrammetric point cloud products into homogeneous and spatially connected elements. In specific, a knowledge-based ruleset has been developed in accordance with the local morphometric parameters. Orthomosaic and DSM were segmented in meaningful objects based on a number of geometrical and contextual properties and classified as a landslide object (scarp, depletion zone, accumulation zone). The resulted models were used to detect and characterize 3D landslide features and provide a hazard assessment in respect to the road network. Moreover, a detailed assessment of the identified failure mechanism has been provided. The proposed study presents the effectiveness and efficiency of UAV platforms to acquire accurate photogrammetric datasets from high-mountain environments and complex surface topographies and provide a holistic object-based framework to characterize the failure site based on semantic classification of the landslide objects.

Structural mapping of rock walls imaged with a LiDAR mounted on an unmanned aircraft system

Structural mapping of rock walls to determine fracture orientation provides critical geological information in support of mining operations. A helicopter-style UAS (rotor diameter 2 m; take-off mass 35 kg; payload mass 11 kg) instrumented with a high-resolution LiDAR imaged a 75 m long and 10–15 m high series of four adjacent rock walls at the Canadian Wollastonite mine. A point cloud with a density of 484 point/m2 acquired at an angle of incidence of ∼41.7° from a flight altitude of 41.7 m above ground level was selected for structural mapping. The point cloud was first meshed using the Poisson surface reconstruction method and then remeshed to achieve an even element size distribution. Visualization of the remeshed Poisson mesh using a 360° hue–saturation–lightness colour wheel highlighted areas of higher fracture density, whereas visualization using a 180° colour wheel accentuated sliver-like geological features. Two joint sets were identified at 156/82 and 241/86 (strike/dip in degrees). A total of 18 virtual strike measurements and 13 virtual dip measurements were within 10% of manual compass measurements. This study demonstrated that the task of structural mapping of large rock walls can be automated by processing 3D images acquired with a LiDAR mounted on a UAS.

Calibration of magnetic compass using an improved extreme learning machine based on reverse tuning

PurposeThe sources of magnetic sensors errors are numerous, such as currents around, soft magnetic and hard magnetic materials and so on. The traditional methods mainly use explicit error models, and it is difficult to include all interference factors. This paper aims to present an implicit error model and studies its high-precision training method.Design/methodology/approachA multi-level extreme learning machine based on reverse tuning (MR-ELM) is presented to compensate for magnetic compass measurement errors by increasing the depth of the network. To ensure the real-time performance of the algorithm, the network structure is fixed to two ELM levels, and the maximum number of levels and neurons will not be continuously increased. The parameters of MR-ELM are further modified by reverse tuning to ensure network accuracy. Because the parameters of the network have been basically determined by least squares, the number of iterations is far less than that in the traditional BP neural network, and the real-time can still be guaranteed.FindingsThe results show that the training time of the MR-ELM is 19.65 s, which is about four times that of the fixed extreme learning algorithm, but training accuracy and generalization performance of the error model are better. The heading error is reduced from the pre-compensation ±2.5° to ±0.125°, and the root mean square error is 0.055°, which is about 0.46 times that of the fixed extreme learning algorithm.Originality/valueMR-ELM is presented to compensate for magnetic compass measurement errors by increasing the depth of the network. In this case, the multi-level ELM network parameters are further modified by reverse tuning to ensure network accuracy. Because the parameters of the network have been basically determined by least squares, the number of iterations is far less than that in the traditional BP neural network, and the real-time training can still be guaranteed. The revised manuscript improved the ELM algorithm itself (referred to as MR-ELM) and bring new ideas to the peers in the magnetic compass error compensation field.

Structure from Motion photogrammetry to characterize underground rock masses: Experiences from two real tunnels

A new methodology to identify discontinuity sets at the tunnel face based on the Structure from Motion (SfM) photogrammetric technique is proposed. The work focuses on the performance of this technique when employed to characterize the ground mass under real tunneling conditions, illustrating its possibilities and analyzing several aspects that affect the quality of the obtained results. By means of a set of overlapping photographs from the tunnel face, SfM constructs a 3D point cloud model, from which discontinuities are identified using a discontinuity set extractor software. To orientate and scale the digital model, an easy-to-use “portable orientation template”, specifically developed for this work, is employed. The proposed methodology is applied to two real tunnels under construction in Northern Spain. Its results are compared with those obtained with a traditional analysis based on manual compass measurements. Results show that the SfM methodology provides an adequate characterization of the structure of the rock mass, identifying the same number of discontinuity sets as the compass measurements approach and with differences in orientation that are within the uncertainty range associated to manual measurements. Only one sub-horizontal set presented higher orientation differences, but this is mainly due to the presence of shotcrete at the face. In addition to the advantages of a “distant” measurement technique—e.g., health and safety advantages, capability to characterize unreachable areas, etc.—, as well as to the advantage of its reduced cost, the proposed SfM methodology and its associated tools allow one to represent planes associated to each discontinuity set back into the original 3D digital point model, and to perform detailed analyses that clarify and improve the obtained results. Finally, an analysis about the minimum number of photographs needed to adequately characterize the tunnel face is conducted, with results showing that around 15 good quality photographs are enough for tunnel faces with excavated areas of about 50 m2.

Fast Autonomous Flight in Warehouses for Inventory Applications

The past years have shown a remarkable growth in use-cases for micro aerial vehicles (MAVs). Conceivable indoor applications require highly robust environment perception, fast reaction to changing situations, and stable navigation, but reliable sources of absolute positioning like GNSS or compass measurements are unavailable during indoor flights. We present a high-performance autonomous inventory MAV for operation inside warehouses. The MAV navigates along warehouse aisles and detects the placed stock in the shelves alongside its path with a multimodal sensor setup containing an RFID reader and two high-resolution cameras. We describe in detail the SLAM pipeline based on a 3D lidar, the setup for stock recognition, the mission planning and trajectory generation, as well as a low-level routine for avoidance of dynamical or previously unobserved obstacles. Experiments were performed in an operative warehouse of a logistics provider, in which an external warehouse management system provided the MAV with high-level inspection missions that are executed fully autonomously.

Validation of fracture data recognition in rock masses by automated plane detection in 3D point clouds

This paper presents (1) an automated method to extract planes and their spatial orientation directly from 3D point clouds, followed by (2) extensive validation tests accompanied by thorough statistical analysis, and (3) a fracture intensity calculation on automatically segmented planes. For the plane extraction, a region growing segmentation algorithm controlled by several input parameters is applied to a point cloud of a granite outcrop. Within its complex surface shape, more than 1000 compass measurements were conducted for validation. In addition, digitally handpicked planes in the software Virtual Reality Geological Studio (VRGS) were used for single plane comparison. In a second test site, we performed fracture intensity calculation in Petrel based on results of the segmentation algorithm on mechanical layers of a clastic sedimentary succession. The comparison of automated segmentation results and compass measurements of three different plane sets shows a deviation of 0.70–2.00°, while the mean single plane divergence amounts to 4.97°. Hence, this study presents a fast, precise, and highly adaptable automated plane detection method, which is reproducible, transparent, objective, and provides increased accuracy in outcrops with rough and complex surfaces. Moreover, output formats of spatial orientation and location of planes are designed for simple handling in other workflows and software.

Modern approaches to field data collection and mapping: Digital methods, crowdsourcing, and the future of statistical analyses

Modern use of mobile devices for field geology has facilitated new approaches to, and methodologies for, field data collection. Here, we highlight current, state-of-the-art methods, including digital-compass measurements and field data collection with mobile devices, which facilitate crowdsourcing by novice geologists. Crowd-sourced collection of field data is advocated as a means of assembling big datasets for the construction of detailed geologic maps. However, expert control of field data is necessary to address inconsistencies in crowd-sourced novice datasets. Digital compasses on mobile devices can facilitate collection of field data by less-experienced geologists. However, concerns exist regarding instrument-related data quality. We incorporate discussions of statistical methods that are relevant to evaluating the precision and accuracy of digital compasses as compared with analogue compasses. All compass platforms tested (Brunton Pocket Transits, iPhones, iPads, and Android-based phones) exhibited inconstancies in precision. However, the least reliable were Android-based devices. We argue that redundancy in measurements, coupled with assessing instrument drift through time, is necessary for all types of compasses. Statistical evaluation of compass measurements and other field data is arguably an important component of future mapping and data collection methods, as we adapt to the opportunities and challenges of assembling massive field datasets.

Robust Self-Contained Pedestrian Navigation by Fusing the IMU and Compass Measurements via UFIR Filtering

In order to overcome the poor observability of yaw measurement for foot-mounted inertial measurement unit (IMU), an integrated IMU+Compass scheme for self-contained pedestrian navigation is presented. In this mode, the compass measurement is used to provide the accurate yaw to improve the accuracy of the attitude transformation matrix for the foot-mounted IMU solution. And then, when the person is in a stance phase during walk, a unbiased finite impulse response (UFIR) filter based on the self-contained pedestrian navigation scheme is investigated, which just needs the state vector size MU and the filtering horizon size NU, while ignoring the noise statistics compared with the Kalman filter (KF). Finally, a real test has been done to verify the performance of the proposed self-contained pedestrian navigation using the IMU and compass measurements via UFIR filter. The test results show that the proposed filter has robust performance compared with the KF.

Sivers asymmetry in the pion induced Drell-Yan process at COMPASS within transverse momentum dependent factorization

We investigate the Sivers asymmetry in the pion-induced single polarized Drell-Yan process in the theoretical framework of the transverse momentum dependent factorization up to next-to-leading logarithmic order of QCD. Within the TMD evolution formalism of parton distribution functions, the recently extracted nonperturbative Sudakov form factor for the pion distribution functions as well as the one for the Sivers function of the proton are applied to numerically estimate the Sivers asymmetry in the $\pi^- p$ Drell-Yan at the kinematics of the COMPASS at CERN. In the low $b$ region, the Sivers function in $b$-space can be expressed as the convolution of the perturbatively calculable hard coefficients and the corresponding collinear correlation function, of which the Qiu-Sterman function is the most relevant one. The effect of the energy-scale dependence of the Qiu-Sterman function to the asymmetry is also studied. We find that our prediction on the Sivers asymmetries as functions of $x_p$, $x_\pi$, $x_F$ and $q_\perp$ is consistent with the recent COMPASS measurement.

Dispersion relations for hadronic light-by-light scattering and the muon g – 2

The largest uncertainties in the Standard Model calculation of the anomalous magnetic moment of the muon (g – 2)μ come from hadronic effects, and in a few years the subleading hadronic light-by-light (HLbL) contribution might dominate the theory error. We present a dispersive description of the HLbL tensor, which is based on unitarity, analyticity, crossing symmetry, and gauge invariance. This opens up the possibility of a data-driven determination of the HLbL contribution to (g – 2)μ with the aim of reducing model dependence and achieving a reliable error estimate. Our dispersive approach defines unambiguously the pion-pole and the pion-box contribution to the HLbL tensor. Using Mandelstam double-spectral representation, we have proven that the pion-box contribution coincides exactly with the one-loop scalar-QED amplitude, multiplied by the appropriate pion vector form factors. Using dispersive fits to high-statistics data for the pion vector form factor, we obtain [see formula in PDF]. A first model-independent calculation of effects of ππ intermediate states that go beyond the scalar-QED pion loop is also presented. We combine our dispersive description of the HLbL tensor with a partial-wave expansion and demonstrate that the known scalar-QED result is recovered after partial-wave resummation. After constructing suitable input for the γ*γ* → ππ helicity partial waves based on a pion-pole left-hand cut (LHC), we find that for the dominant charged-pion contribution this representation is consistent with the two-loop chiral prediction and the COMPASS measurement for the pion polarizability. This allows us to reliably estimate S-wave rescattering effects to the full pion box and leads to [see formula in PDF].

Recent COMPASS results on Transverse Spin Asymmetries in SIDIS

After reviewing the most important COMPASS results on transverse spin effects in SIDIS, I will present the recent work we have done on weighted Sivers asymmetries and “transversity induced” Λ polarisation. Using the high statistics data collected in 2010 on a transversely polarised proton target COMPASS has evaluated the transverse momentum weighted Sivers asymmetries both in x- and in z-bins. The results are also compared with the standard unweighted asymmetries. Using the whole data sample collected over the years on transversely polarised deuteron and proton targets COMPASS has measured the transversity induced Λ polarisation in the reaction μN → μ′ΛX. Possible future SIDIS COMPASS measurements will also be briefly mentioned.

MPGD-based photon detector upgrade for COMPASS RICH

The RICH detector of the COMPASS Experiment at CERN SPS is undergoing an important upgrade: the central MWPC-based photon detectors have been replaced with novel Micropattern detectors, to cope with the challenging efficiency and stability requirements of the new COMPASS measurements. The new hybrid MPGD detector consists of two layers of ThickGEMs and a capacitive bulk Micromegas. Photoconversion takes place on the CsI layer deposited onto the first ThickGEM, while position information and signals are read out from the pad-segmented anode via capacitive coupling by analog front-end electronics based on APV25 chips. The paper focuses on the main issues of production, detailed quality assessment technique, and the commissioning status of the first in-experiment MPGD-based photon detectors for RICH application.

Rescattering Effects in the Hadronic-Light-by-Light Contribution to the Anomalous Magnetic Moment of the Muon.

We present a first model-independent calculation of ππ intermediate states in the hadronic-light-by-light (HLBL) contribution to the anomalous magnetic moment of the muon (g-2)_{μ} that goes beyond the scalar QED pion loop. To this end, we combine a recently developed dispersive description of the HLBL tensor with a partial-wave expansion and demonstrate that the known scalar-QED result is recovered after partial-wave resummation. Using dispersive fits to high-statistics data for the pion vector form factor, we provide an evaluation of the full pion box a_{μ}^{π box}=-15.9(2)×10^{-11}. We then construct a suitable input for the γ^{*}γ^{*}→ππ helicity partial waves, based on a pion-pole left-hand cut and show that for the dominant charged-pion contribution, this representation is consistent with the two-loop chiral prediction and the COMPASS measurement for the pion polarizability. This allows us to reliably estimate S-wave rescattering effects to the full pion box and leads to our final estimate for the sum of these two contributions a_{μ}^{π box}+a_{μ,J=0}^{ππ,π-pole LHC}=-24(1)×10^{-11}.

The COMPASS Measurement of the Pion Polarizability

The COMPASS experiment at CERN reported in a 2015 Physical Review Letter the first precise measurement of the electromagnetic polarizability of the charged pion. After a short introduction of the experiment, we will underline the basic aspects of the measurement of the polarizability performed by COMPASS and the impact of the result.