diff --git a/geoprob_pipe/calculations/systems/moria/initial_input.py b/geoprob_pipe/calculations/systems/moria/initial_input.py
index 877b9178..46e69f93 100644
--- a/geoprob_pipe/calculations/systems/moria/initial_input.py
+++ b/geoprob_pipe/calculations/systems/moria/initial_input.py
@@ -276,7 +276,7 @@
         "remark": "",
         "unit": "kN/m³",
         "distribution_type": DistributionType.deterministic,
-        "mean": 16.5,
+        "mean": 26.0,
         "source": "excel",
     },
     {
diff --git a/geoprob_pipe/calculations/systems/wbi/initial_input.py b/geoprob_pipe/calculations/systems/wbi/initial_input.py
index d3285ac1..9065d42a 100644
--- a/geoprob_pipe/calculations/systems/wbi/initial_input.py
+++ b/geoprob_pipe/calculations/systems/wbi/initial_input.py
@@ -239,7 +239,7 @@
         "remark": "",
         "unit": "kN/m³",
         "distribution_type": DistributionType.deterministic,
-        "mean": 16.5,
+        "mean": 26.0,
         "source": "excel",
     },
     {
diff --git a/geoprob_pipe/changelog.py b/geoprob_pipe/changelog.py
index e3fa28a7..e4ae840e 100644
--- a/geoprob_pipe/changelog.py
+++ b/geoprob_pipe/changelog.py
@@ -1,5 +1,9 @@
 
 CHANGELOG = {
+    "2.2.10":
+        "Bug fix en added validation. Traject probability of failure kon net boven 1.0 uitkomen door de toegepaste "
+        "rekentechniek. Daarnaast om het gebruik van de applicatie te verbeteren extra validatie toegepast, zoals dat "
+        "de vakindeling gezamenlijk één lijn moet zijn (zonder onderbrekingen).",
     "2.2.3":
         "Bug fix. Validation issue.",
     "2.2.0":
diff --git a/geoprob_pipe/cmd_app/parameter_input/input_parameter_tables.py b/geoprob_pipe/cmd_app/parameter_input/input_parameter_tables.py
index 15062cfa..6bf15201 100644
--- a/geoprob_pipe/cmd_app/parameter_input/input_parameter_tables.py
+++ b/geoprob_pipe/cmd_app/parameter_input/input_parameter_tables.py
@@ -37,10 +37,6 @@ def _validate_df_parameter_invoer(df: DataFrame, app_settings: ApplicationSettin
 
     label = "Parameter invoer"
 
-    # obj = DataFrameQueryValidation(df=df, failure_queries=FAILURE_QUERIES)
-    # result: bool = obj.validate(export_dir=export_dir, label_humanized="Parameter invoer")
-    # TODO: Remove FailureQueries-code
-
     # Set up validator
     validator = ValidationParameterInvoer(df=df)
     geohydrologisch_model = app_settings.geohydrologisch_model
diff --git a/geoprob_pipe/cmd_app/spatial_layers/hrd/hrd.py b/geoprob_pipe/cmd_app/spatial_layers/hrd/hrd.py
index 234d01b7..f72a3cf8 100644
--- a/geoprob_pipe/cmd_app/spatial_layers/hrd/hrd.py
+++ b/geoprob_pipe/cmd_app/spatial_layers/hrd/hrd.py
@@ -29,7 +29,7 @@ def _hrd_data_requested(app_settings: ApplicationSettings) -> bool:
     choices_list = ["Ja", "Nee", "Applicatie afsluiten"]
     choice = inquirer.select(
         message=f"Wil je HRD-data importeren? Dit is optioneel. "
-                f"Je kunt ook handmatig overschrijdingsfrequentielijnen toevoegen.",
+                f"Je kunt op een later moment handmatig overschrijdingsfrequentielijnen toevoegen aan de invoer-Excel.",
         choices=choices_list, default=choices_list[0]).execute()
 
     # Close app?
diff --git a/geoprob_pipe/cmd_app/spatial_layers/polderpeil.py b/geoprob_pipe/cmd_app/spatial_layers/polderpeil.py
index ad73a421..3a2cfbe6 100644
--- a/geoprob_pipe/cmd_app/spatial_layers/polderpeil.py
+++ b/geoprob_pipe/cmd_app/spatial_layers/polderpeil.py
@@ -5,6 +5,7 @@
 from shapely import Polygon, MultiPolygon
 from geopandas import GeoDataFrame, read_file
 import fiona
+from geoprob_pipe.input_data.df_validation.df_polderpeilen import ValidationPolderpeilen
 from geoprob_pipe.utils.validation_messages import BColors
 import warnings
 if TYPE_CHECKING:
@@ -58,10 +59,10 @@ def request_polderpeil_filepath(app_settings: ApplicationSettings):
         raise NotImplementedError(
             f"Applicatie vroegtijdig afgesloten: Een {filepath.split(sep='.')[-1]}-bestand is niet geïmplementeerd.")
 
-    # Confirm all are points
-    all_geometries_are_points = gdf.geometry.apply(
+    # Confirm all are polygons
+    all_geometries_are_polygons = gdf.geometry.apply(
         lambda geom: isinstance(geom, Polygon) or isinstance(geom, MultiPolygon)).all()
-    if not all_geometries_are_points:
+    if not all_geometries_are_polygons:
         print(BColors.WARNING, f"Het geïmporteerde bestand bestaat niet (volledig) uit vlakken/polygonen, maar ook uit "
                                f"andere typen geometrie. Enkel vlakken/polygonen zijn toegestaan.", BColors.ENDC)
         request_polderpeil_filepath(app_settings=app_settings)
@@ -143,7 +144,27 @@ def specify_column_with_polderpeil_niveau(app_settings: ApplicationSettings, gdf
             continue
         column_name_is_valid = True
 
+    # Rename columns
     gdf_to_add = gdf[["geometry", column_name]]
     gdf_to_add = gdf_to_add.rename(columns={column_name: "polderpeil"})
-    gdf_to_add.to_file(app_settings.geopackage_filepath, layer="polderpeil", driver="GPKG")
-    print(BColors.OKBLUE, f"✅  Polderpeilen toegevoegd.", BColors.ENDC)
+
+    # Validate input
+    validator = ValidationPolderpeilen(df=gdf_to_add)
+    validator.run()
+    if validator.df_failures is not None and validator.df_failures.__len__() > 0:
+        export_dir: str = os.path.join(
+            app_settings.workspace_dir,
+            "exports",
+            app_settings.datetime_stamp,
+            "parameter_input_process")
+        os.makedirs(export_dir, exist_ok=True)
+        export_path: str = os.path.join(export_dir, "validation_messages_polderpeilen.xlsx")
+        validator.df_failures.to_excel(export_path)
+        print(BColors.WARNING, f"Het valideren van de polderpeil-data resulteerde in validatieberichten. Zorg dat "
+                               f"deze eerst opgelost zijn. De validatieberichten zijn hiernaartoe geëxporteerd: "
+                               f"{export_path}.", BColors.ENDC)
+        request_polderpeil_filepath(app_settings=app_settings)
+    else:
+        # Add to geopackage
+        gdf_to_add.to_file(app_settings.geopackage_filepath, layer="polderpeil", driver="GPKG")
+        print(BColors.OKBLUE, f"✅  Polderpeilen toegevoegd.", BColors.ENDC)
diff --git a/geoprob_pipe/cmd_app/spatial_layers/vakindeling.py b/geoprob_pipe/cmd_app/spatial_layers/vakindeling.py
index eb40641c..e50b5172 100644
--- a/geoprob_pipe/cmd_app/spatial_layers/vakindeling.py
+++ b/geoprob_pipe/cmd_app/spatial_layers/vakindeling.py
@@ -3,7 +3,8 @@
 from InquirerPy import inquirer
 import warnings
 from geoprob_pipe.cmd_app.utils.spatial import load_dijktraject_linestring
-from geoprob_pipe.utils.gdf import convert_mls_geom_column_to_ls
+from geoprob_pipe.utils.gdf import (
+    convert_mls_geom_column_to_ls, validate_geometry_types, validate_vakindeling_merges_to_single_linestring)
 import os
 from pathlib import Path
 from shapely import LineString, MultiLineString
@@ -144,10 +145,29 @@ def request_vakindeling_filepath(app_settings: ApplicationSettings):
 def validate_vakindeling(app_settings: ApplicationSettings, gdf: GeoDataFrame):
     """ Validates the vakindeling shape, with some conversions if they can be
     applied safely. """
+
+    # Validate geometry types
+    allowed_types = {"LineString", "MultiLineString"}
+    valid, invalid_types = validate_geometry_types(gdf=gdf, allowed_types=allowed_types)
+    assert valid, (f"De opgegeven vakindeling heeft geometrie types die niet toegestaan zijn. De volgende types zijn "
+                   f"toegestaan: {allowed_types}. De volgende niet toegestane types werden ook gevonden: "
+                   f"{invalid_types}. "
+                   f"Zorg er voor dat je alleen line strings importeert.")
+
+    # Convergeer multi line strings naar single line strings
     gdf = convert_mls_geom_column_to_ls(gdf=gdf)
+
+    # Controleer of elk vak een geometrie heeft
     assert gdf.geometry.apply(lambda geom: isinstance(geom, LineString)).all(), \
         ("De opgegeven vakindeling heeft niet voor elk vak een geometry. De "
          "applicatie sluit nu af.")
+
+    # Check if vakindeling does not have gaps
+    valid, merged_type = validate_vakindeling_merges_to_single_linestring(gdf=gdf)
+    assert valid, (f"De vakindeling is niet valide. Ter controle is een poging gedaan of de vakindeling "
+                   f"samenvoegbaar is tot één lijn. Dit blijkt niet het geval. Zitten er gaten tussen de vakken?")
+
+    # Continue questioner
     specify_column_with_vaknaam(app_settings, gdf=gdf)
 
 
@@ -286,6 +306,12 @@ def align_vak_shp_to_dijktraject(
     gdf_new_vakindeling: GeoDataFrame = gdf_new_vakindeling[
         ["id", "naam", "m_start", "m_end", "geometry"]]
 
+    # Validate correct geometry types
+    valid, invalid_types = validate_geometry_types(gdf=gdf_new_vakindeling, allowed_types={"LineString"})
+    assert valid, (f"Most probably a bug. Invalid geometry types resulted from projecting the imported vakindeling "
+                   f"to the dijktraject-geometry. The invalid geometry types are {invalid_types}. Only LineStrings "
+                   f"were expected. Re-examine your input, or contact a developer with this error.")
+
     # Add to geopackage
     gdf_new_vakindeling.to_file(
         Path(app_settings.geopackage_filepath),
diff --git a/geoprob_pipe/input_data/df_validation/df_polderpeilen.py b/geoprob_pipe/input_data/df_validation/df_polderpeilen.py
new file mode 100644
index 00000000..462e90ad
--- /dev/null
+++ b/geoprob_pipe/input_data/df_validation/df_polderpeilen.py
@@ -0,0 +1,27 @@
+from geoprob_pipe.utils.df_validation import (
+    DataFrameValidation, ColumnValidation, ValidationRequirement, requirements)
+from pandas import DataFrame
+
+
+POLDERPEIL = ColumnValidation(column_name="polderpeil", requirements=[
+    ValidationRequirement(
+        requirement=requirements.is_not_null,
+        failure_msg=f"De waarde van het polderpeil moet ingevuld zijn met een numerieke waarde. Eén of meerdere "
+                    f"rijen heeft geen waarde."),
+    ValidationRequirement(
+        requirement=requirements.is_numeric,
+        failure_msg=f"De waarde van het polderpeil moet een numerieke waarde hebben. Eén of meerdere rijen voldoet "
+                    f"hier niet aan. ",
+    ),
+    requirements.IsInRange(left=-99, right=999),
+])
+
+class ValidationPolderpeilen(DataFrameValidation):
+
+    def __init__(self, df: DataFrame):
+        super().__init__(
+            df=df,
+            label="Polderpeilen",
+            required_columns=[],
+            columns_validations=[POLDERPEIL]
+        )
diff --git a/geoprob_pipe/input_data/validation/__init__.py b/geoprob_pipe/input_data/validation/__init__.py
deleted file mode 100644
index e69de29b..00000000
diff --git a/geoprob_pipe/input_data/validation/dataframes/__init__.py b/geoprob_pipe/input_data/validation/dataframes/__init__.py
deleted file mode 100644
index e69de29b..00000000
diff --git a/geoprob_pipe/input_data/validation/dataframes/df_parameter_invoer.py b/geoprob_pipe/input_data/validation/dataframes/df_parameter_invoer.py
deleted file mode 100644
index 4f2363ab..00000000
--- a/geoprob_pipe/input_data/validation/dataframes/df_parameter_invoer.py
+++ /dev/null
@@ -1,40 +0,0 @@
-from typing import List
-from geoprob_pipe.input_data.validation.dataframes.validation_objects import FailureQuery
-
-
-FAILURE_QUERIES: List[FailureQuery] = [
-
-    # Kolom 'scope'
-    FailureQuery(
-        query="scope in ['traject', 'vak', 'uittredepunt']",
-        msg="De scope moet 'traject', 'vak' of 'uittredepunt' zijn."),
-
-    # Kolom 'scope_referentie'
-    FailureQuery(
-        query="scope in ['vak', 'uittredepunt'] and scope_referentie.isnull()",
-        msg="De scope referentie moet worden gespecificeerd wanneer de scope 'vak' of 'uittredepunt' is."),
-
-    # Kolom 'mean'
-    FailureQuery(
-        query="distribution_type in ['normal', 'log_normal'] and mean.isnull()",
-        msg="Geen gemiddelde waarde gespecificeerd voor deze rij. Dit is vereist bij distributie types 'normal' en "
-            "'log_normal'."),
-    FailureQuery(
-        query="parameter in ['d70', 'd70_m'] "
-              "and distribution_type in ['deterministic', 'log_normal', 'normal'] "
-              "and mean >= 0.001",
-        msg="Parameter d70/d70_m moet een waarde hebben die kleiner is dan 0.001. Deze geef je op in de eenheid "
-            "meters. Wellicht is de eenheid van de opgegeven waarde verkeerd?"),
-
-    # Kolom 'variation' en 'deviation'
-    FailureQuery(
-        query="distribution_type in ['normal', 'log_normal'] and variation.isnull() and deviation.isnull()",
-        msg="Geen variatie coefficient of standaard deviatie gespecificeerd voor deze rij. Dit is vereist bij "
-            "distributie types 'normal' en 'log_normal'."),
-
-    # Kolom 'fragility_values_ref'
-    FailureQuery(
-        query="distribution_type == 'cdf_curve' and fragility_values_ref.isnull()",
-        msg="Geen referentie naar de fragility values gespecificeerd voor deze rij. Dit is vereist bij distributie "
-            "type 'cdf_curve'."),
-]
diff --git a/geoprob_pipe/input_data/validation/dataframes/df_scenario_invoer_som_kans.py b/geoprob_pipe/input_data/validation/dataframes/df_scenario_invoer_som_kans.py
deleted file mode 100644
index b6d01088..00000000
--- a/geoprob_pipe/input_data/validation/dataframes/df_scenario_invoer_som_kans.py
+++ /dev/null
@@ -1,19 +0,0 @@
-from typing import List
-from geoprob_pipe.input_data.validation.dataframes.validation_objects import FailureQuery
-from pandas import DataFrame
-
-
-def _df_scenario_group_sum_kans(df: DataFrame) -> DataFrame:
-    df_grouped: DataFrame = df.groupby(["vak_id"], as_index=False)["kans"].sum()
-    df_grouped = df_grouped.rename(columns={"kans": "som_kans"})
-    df_grouped["som_kans"] = df_grouped["som_kans"].round(3)
-    return df_grouped
-
-
-FAILURE_QUERIES: List[FailureQuery] = [
-    FailureQuery(
-        query="som_kans != 1.0",
-        msg="In de tabel 'Scenario invoer' moet de som van de kansen gelijk zijn aan 1.0 (100%). "
-            "Dit is niet het geval voor dit vak."
-    ),
-]
diff --git a/geoprob_pipe/input_data/validation/dataframes/validation_objects.py b/geoprob_pipe/input_data/validation/dataframes/validation_objects.py
deleted file mode 100644
index c3afacd1..00000000
--- a/geoprob_pipe/input_data/validation/dataframes/validation_objects.py
+++ /dev/null
@@ -1,51 +0,0 @@
-from typing import List
-from pandas import DataFrame
-import os
-from dataclasses import dataclass
-from geoprob_pipe.utils.validation_messages import BColors
-
-
-@dataclass
-class FailureQuery:
-    query: str
-    msg: str
-
-
-class DataFrameQueryValidation:
-
-    def __init__(self, df: DataFrame, failure_queries: List[FailureQuery]):
-        self.df = df
-        self.failure_queries = failure_queries
-
-    def validate(self, export_dir: str, label_humanized: str) -> bool:
-        for failure_query in self.failure_queries:
-
-            # Assess
-            df_failure_rows: DataFrame = self.df.query(failure_query.query)
-            df_failure_rows = df_failure_rows.copy(deep=True)
-
-            # Continue if no failures
-            if df_failure_rows.__len__() == 0:
-                continue
-
-            # Prepare dataframe for export
-            current_columns = df_failure_rows.columns
-            new_column_order = ["validation_msg", "tabel"]
-            new_column_order.extend(current_columns)
-            df_failure_rows['validation_msg'] = failure_query.msg
-            df_failure_rows['tabel'] = label_humanized
-            df_failure_rows = df_failure_rows[new_column_order]
-
-            # Report back
-            os.makedirs(export_dir, exist_ok=True)
-            export_path = os.path.join(export_dir, "df_failure_rows.xlsx")
-            if os.path.exists(export_path):
-                os.remove(export_path)
-            df_failure_rows.to_excel(export_path, index=False)
-            print(f"{BColors.WARNING}Validatie is (voortijdig) beëindigd omdat er {df_failure_rows.__len__()} "
-                  f"validatie issues voor de '{label_humanized}'-tabel zijn gevonden. De gedetailleerde lijst is "
-                  f"geëxporteerd naar onderstaande locatie. Los deze issues s.v.p. eerst op. \n"
-                  f"{export_path}{BColors.ENDC}")
-            return False
-
-        return True
diff --git a/geoprob_pipe/results/assemblage/functions.py b/geoprob_pipe/results/assemblage/functions.py
index c3db7dd3..2ba7f72c 100644
--- a/geoprob_pipe/results/assemblage/functions.py
+++ b/geoprob_pipe/results/assemblage/functions.py
@@ -17,7 +17,7 @@ def combine_series(list_pf: list[float]) -> Tuple[float, float]:
        doorsneden.
 
     :param list_pf: Lijst met faalkansen van de elementen.
-    :return bovengrens en ondergrens
+    :return: bovengrens en ondergrens
     """
 
     # If empty
@@ -28,7 +28,7 @@ def combine_series(list_pf: list[float]) -> Tuple[float, float]:
     ondergrens = max(list_pf)
 
     # We have to use Decimal for bovengrens
-    getcontext().prec = 30
+    getcontext().prec = 100
     # Because with small numbers (e-18 and smaller) it turns out that 1 - e-18 is rounded to one. Therefore, we have to
     # use Decimal with a lowered precision (we use up to e-30). We now first convert the necessary values to Decimal:
     one = Decimal(1)
@@ -111,22 +111,18 @@ def window_collect(window_size: float, point_list: list[UittredepuntElement],
     bins_window = np.arange(
         m_van, m_tot, window_size
         ).tolist()
-    bins_window.append(m_tot)
+    if m_tot not in bins_window:
+        bins_window.append(m_tot)  # add end of final window
 
     bin_cat: pd.Categorical = cast(pd.Categorical, pd.cut(
-        list_m_value,
-        bins=bins_window,
-        right=False,
-        include_lowest=True
-        ))
+        list_m_value, bins=bins_window, right=False, include_lowest=True, duplicates="drop"))
     df_vak = df_vak.assign(bin=bin_cat)
     df_bin = (df_vak.groupby("bin", observed=False)["pf"].max()
               .reindex(bin_cat.categories).fillna(0))
 
     sum_pf, max_pf = combine_series(df_bin.to_list())
     window_elements: List[WindowElement] = []
-    bins_window.append(m_tot)  # add end of final window
-    for i in range(len(bins_window)-2):
+    for i in range(len(bins_window)-1):
         window_elements.append(WindowElement(
             m_van=bins_window[i],
             m_tot=bins_window[i+1],
@@ -164,7 +160,7 @@ def scaled_collect(
         windows.
     """
     from geoprob_pipe.results.assemblage.objects import WindowElement
-    if point_list.__len__() == 0:  # Leeg element
+    if len(point_list) == 0:  # Leeg element
         return 0.0, 0.0, []
     fcn_list = [p.flow_chart_number for p in point_list]
     if min(fcn_list) == 11:
@@ -214,7 +210,7 @@ def scaled_collect(
         length = seg_end - seg_start
         a = sel.a
         N_vak = bepaal_N_vak(length, a, dL)
-        pf = cast(float, sel.pf) * N_vak
+        pf = min(1.0, cast(float, sel.pf) * N_vak)  # Limiet als pf zeer hoog is.
         pfs.append(pf)
         window_elements.append(
             WindowElement(
diff --git a/geoprob_pipe/results/assemblage/objects.py b/geoprob_pipe/results/assemblage/objects.py
index cb8f1ad5..b26b5c12 100644
--- a/geoprob_pipe/results/assemblage/objects.py
+++ b/geoprob_pipe/results/assemblage/objects.py
@@ -25,13 +25,13 @@ def __post_init__(self):
 
         if self.pf is not None:
             if not (0.0 <= self.pf <= 1.0):
-                raise ValueError("pof moet tussen 0.0 en 1.0 liggen.")
+                raise ValueError(f"pof moet tussen 0.0 en 1.0 liggen. Huidige waarde is {self.pf}")
 
-        if self.beta is not None:
-            if not math.isfinite(self.beta):
-                raise ValueError("beta moet een eindige waarde zijn.")
-            if (-38.0 <= self.beta <= 38.0) is False:
-                raise ValueError("beta moet tussen -38.0 en 38.0 liggen.")
+        # if self.beta is not None:
+        #     if not math.isfinite(self.beta):
+        #         raise ValueError("beta moet een eindige waarde zijn.")
+        #     if (-38.0 <= self.beta <= 38.0) is False:
+        #         raise ValueError("beta moet tussen -38.0 en 38.0 liggen.")
 
         if self.pf is None and self.beta is not None:
             self.pf = float(stats.norm.cdf(-1.0 * self.beta))
@@ -56,13 +56,13 @@ def __post_init__(self):
 
         if self.pf is not None:
             if not (0.0 <= self.pf <= 1.0):
-                raise ValueError("pof moet tussen 0.0 en 1.0 liggen.")
+                raise ValueError(f"pof moet tussen 0.0 en 1.0 liggen. Huidige waarde is {self.pf}")
 
-        if self.beta is not None:
-            if not math.isfinite(self.beta):
-                raise ValueError("beta moet een eindige waarde zijn.")
-            if (-38.0 <= self.beta <= 38.0) is False:
-                raise ValueError("beta moet tussen -38.0 en 38.0 liggen.")
+        # if self.beta is not None:
+        #     if not math.isfinite(self.beta):
+        #         raise ValueError("beta moet een eindige waarde zijn.")
+        #     if (-38.0 <= self.beta <= 38.0) is False:
+        #         raise ValueError("beta moet tussen -38.0 en 38.0 liggen.")
 
         if self.pf is None and self.beta is not None:
             self.pf = float(stats.norm.cdf(-1.0 * self.beta))
@@ -121,7 +121,8 @@ def pf_max_dsn(self) -> Tuple[KansElement, KansElement]:
             pf_dsn = max(list_pf)
 
         # Bereken vak kans
-        pf_vak = self.N_vak * pf_dsn
+        # pf_vak = self.N_vak * pf_dsn
+        pf_vak = min(1.0, self.N_vak * pf_dsn)  # Limit naar 1 bij zeer hoge pof.
 
         return KansElement(pf=pf_dsn), KansElement(pf=pf_vak)
 
@@ -131,7 +132,7 @@ def conv_max_dsn(self) -> bool:
         kansen geconvergeerd zijn, dan True, anders False. Want een niet geconvergeerde kans had de maximale faalkans
         kunnen zijn. """
         list_conv = [cast(bool, dsn.converged) for dsn in self.dsn_list]
-        if False in list_conv:
+        if all(list_conv):
             return False
         return True
 
diff --git a/geoprob_pipe/results/construct_dataframes.py b/geoprob_pipe/results/construct_dataframes.py
index 63a0f42d..d0172423 100644
--- a/geoprob_pipe/results/construct_dataframes.py
+++ b/geoprob_pipe/results/construct_dataframes.py
@@ -1,18 +1,23 @@
 from __future__ import annotations
-from geoprob_pipe.utils.statistics import convert_failure_probability_to_beta
+import operator
+from decimal import Decimal, getcontext
+from functools import reduce
+import numpy as np
 import pandas as pd
-from geoprob_pipe.results.assemblage.objects import (
-    UittredepuntElement, VakElement, TrajectElement)
 from pandas import DataFrame, concat
-import numpy as np
+from geoprob_pipe.results.assemblage.objects import TrajectElement, UittredepuntElement, VakElement
+from geoprob_pipe.utils.statistics import convert_failure_probability_to_beta
 from typing import TYPE_CHECKING, List
 if TYPE_CHECKING:
     from geoprob_pipe.results import Results
     from geoprob_pipe import GeoProbPipe
-    from geoprob_pipe.calculations.systems.base_objects.system_calculation import \
-        SystemCalculation
+    from geoprob_pipe.calculations.systems.base_objects.system_calculation import SystemCalculation
     from probabilistic_library import DesignPoint
     from geoprob_pipe.calculations.systems.build_and_run import CalcResult
+    from geoprob_pipe import GeoProbPipe
+    from geoprob_pipe.calculations.systems.base_objects.system_calculation import SystemCalculation
+    from geoprob_pipe.calculations.systems.build_and_run import CalcResult
+    from geoprob_pipe.results import Results
 
 
 def collect_df_beta_limit_state(calculation: SystemCalculation) -> DataFrame:
@@ -196,12 +201,39 @@ def calculate_df_beta_per_uittredepunt(geoprob_pipe: GeoProbPipe, results: Resul
 
     df_beta_scenarios_final = results.df_beta_scenarios_final.copy(deep=True)
 
-    df = df_beta_scenarios_final.assign(
-        failure_probability=df_beta_scenarios_final.apply(
-            lambda row: row['failure_probability'] * geoprob_pipe.input_data.scenarios.scenario_kans(
-                vak_id=row['vak_id'], scenario_naam=row['ondergrondscenario_id']
-            ), axis=1)).groupby('uittredepunt_id', as_index=False)[
-        'failure_probability'].sum()
+    # The sum() leads to failure probabilities of larger than 1. Due to very small
+    # values decimal is used.
+    getcontext().prec = 100
+    one = Decimal(1)
+    df = (
+        df_beta_scenarios_final.assign(
+            failure_probability=lambda row: (
+                    row["failure_probability"]
+                    * row.apply(
+                lambda row2: (
+                    geoprob_pipe.input_data.scenarios.scenario_kans(
+                        vak_id=row2["vak_id"],
+                        scenario_naam=row2["ondergrondscenario_id"],
+                    )
+                ),
+                axis=1,
+            )
+            )
+        )
+        .groupby("uittredepunt_id", as_index=False)
+        .agg(
+            failure_probability=(
+                "failure_probability",
+                lambda x: float(
+                    one
+                    - reduce(
+                        operator.mul, (one - Decimal(str(v)) for v in x), one
+                    )
+                ),
+            )
+        )
+    )
+
     df["beta"] = df["failure_probability"].apply(lambda failure_prob: convert_failure_probability_to_beta(failure_prob))
 
     # Determine when uittredepunt is converged (when all scenarios are converged)
diff --git a/geoprob_pipe/utils/gdf.py b/geoprob_pipe/utils/gdf.py
index 93467e2f..0cad7a26 100644
--- a/geoprob_pipe/utils/gdf.py
+++ b/geoprob_pipe/utils/gdf.py
@@ -1,5 +1,30 @@
 from geopandas import GeoDataFrame
 from shapely import LineString, MultiLineString
+from typing import List, Tuple
+from shapely import unary_union, line_merge
+
+
+def validate_geometry_types(gdf: GeoDataFrame, allowed_types=None) -> Tuple[bool, List[str]]:
+    """ Controleert of alle geometrieën van een valide type zijn.
+
+    :param gdf:
+    :param allowed_types:
+    :return:
+        1st item: Boolean if valid
+        2nd item: Invalid geometry types
+    """
+
+    # Mutable arguments
+    if allowed_types is None:
+        allowed_types = {"LineString", "MultiLineString"}
+
+    # Validate
+    geom_types = gdf.geometry.geom_type  # of gdf.geom_type
+    mask_invalid = ~geom_types.isin(allowed_types)
+    invalid_gdf = gdf.loc[mask_invalid]
+    is_valid = not mask_invalid.any()
+
+    return is_valid, list(invalid_gdf.geometry.geom_type.unique())
 
 
 def convert_mls_geom_column_to_ls(gdf: GeoDataFrame) -> GeoDataFrame:
@@ -24,3 +49,9 @@ def unwrap_ls_in_mls(geom):
 
     gdf["geometry"] = gdf["geometry"].apply(unwrap_ls_in_mls)
     return gdf
+
+
+def validate_vakindeling_merges_to_single_linestring(gdf: GeoDataFrame) -> Tuple[bool, type]:
+    """ Controleert of alle LineStrings aaneengesloten zijn. """
+    merged = line_merge(unary_union(gdf.geometry))
+    return isinstance(merged, LineString), type(merged)
diff --git a/pyproject.toml b/pyproject.toml
index b7521ec3..a6af3c9b 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -1,7 +1,7 @@
 
 [tool.poetry]
 name = "geoprob_pipe"
-version = "2.2.7"
+version = "2.2.10"
 description = "Execute probabilistic piping calculations using the Deltares probabilic library."
 keywords = [
   "levee",